{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 多元线性回归问题 —— 波士顿房价预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### numpy：\n",
    "* Numpy的核心数据结构，就叫做array数组，array对象可以是一维数组，也可以是多维数组\n",
    "\n",
    "* 相比Python的List,array的优点在于性能好、包含数组元数据信息、大量的便捷函数；\n",
    "\n",
    "* array可以直接逐元素的加减乘除等算数操作,并封装了线性代数函数，比如求解逆矩阵、求解方程组\n",
    "\n",
    "#### matplotlib：\n",
    "* matplotlib 是 Python 最著名的绘图库，\n",
    "* 它提供了一整套和 matlab 相似的命令 API，十分适合交互式地进行制图。而且也可以方便地将它作为绘图控件，嵌入 GUI 应用程序中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 为matplotlib添加中文字体\n",
    "plt.rcParams['axes.unicode_minus']=False #正常显示负数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 收集数据\n",
    "\n",
    "采用任意方法收集数据\n",
    "\n",
    "* Scikit-learn:数据量较小，方便学习\n",
    "网址：http://scikit-learn.org/stable/datasets/index.html\n",
    "* UCI数据集：收录了多种数据集，覆盖科学，生活，经济等领域，数据量几十万。\n",
    "网址：http://archive.ics.uci.edu/ml/\n",
    "* Kaggle数据集：大数据竞赛平台，80万科学家，真是数据，数据量巨大\n",
    "网址：https://www.kaggle.com/datasets\n",
    "\n",
    "house.data:\n",
    "\n",
    "| 面积    | 房间数   |  房价  |\n",
    "| :--------: | :-----:  | :----:  |\n",
    "| 137.97  | 3   |   145.0     |\n",
    "| 104.5  |   2    |   110.0   |\n",
    "| ...  |   ...    |  ... |\n",
    "\n",
    "n = 2\n",
    "\n",
    "m = 16"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 准备数据\n",
    "回归需要数值型数据，标称型数据 (True/False) 将被转化成二值型数据 (1/0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.1 读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "house_mat = []  # 存放房屋属性[面积,房间数]\n",
    "label_mat = []  # 存放房屋价格[房价]\n",
    "with open(\"house.data\",) as fin:\n",
    "    for line in fin:\n",
    "        data_list = line.strip().split(\" \")\n",
    "        data_list = list(filter(None, data_list))\n",
    "        house_data = []\n",
    "        for i in range(len(data_list)-1):\n",
    "            house_data.append(float(data_list[i]))\n",
    "        house_mat.append(house_data)\n",
    "        \n",
    "        label_mat.append(float(data_list[-1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2 将python数组转换为numpy数组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[137.97,   3.  ],\n",
       "       [104.5 ,   2.  ],\n",
       "       [100.  ,   2.  ],\n",
       "       [124.32,   3.  ],\n",
       "       [ 79.2 ,   1.  ],\n",
       "       [ 99.  ,   2.  ],\n",
       "       [124.  ,   3.  ],\n",
       "       [114.  ,   2.  ],\n",
       "       [106.69,   2.  ],\n",
       "       [138.05,   3.  ],\n",
       "       [ 53.75,   1.  ],\n",
       "       [ 46.91,   1.  ],\n",
       "       [ 68.  ,   1.  ],\n",
       "       [ 63.02,   1.  ],\n",
       "       [ 81.26,   2.  ],\n",
       "       [ 86.21,   2.  ]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_mat = np.array(house_mat)\n",
    "house_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[145.  ],\n",
       "       [110.  ],\n",
       "       [ 93.  ],\n",
       "       [116.  ],\n",
       "       [ 65.32],\n",
       "       [104.  ],\n",
       "       [118.  ],\n",
       "       [ 91.  ],\n",
       "       [ 62.  ],\n",
       "       [133.  ],\n",
       "       [ 51.  ],\n",
       "       [ 45.  ],\n",
       "       [ 75.5 ],\n",
       "       [ 69.5 ],\n",
       "       [ 75.69],\n",
       "       [ 95.3 ]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_mat = np.array(label_mat).reshape(-1,1) # 标签向量原本是行向量,转换成列向量\n",
    "label_mat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 分析数据\n",
    "\n",
    "绘出数据的可视化二维图将有助于对数据做出理解和分析，在采用缩减法求得新回归系数之后，可以将新拟合线在图上作为对比"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.1 分析属性和标签的关系\n",
    "\n",
    "绘出 面积-房价 和 房间数-房价 关系图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "\n",
    "plt.subplot(1,2,1)\n",
    "plt.scatter(house_mat[:,0],label_mat)\n",
    "plt.xlabel('面积', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.scatter(house_mat[:,1],label_mat)\n",
    "plt.xlabel('房间数', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.2 分析属性和属性的关系\n",
    "\n",
    "绘出 面积和房间数属性范围的关系图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.bar(['面积','房间数'],[house_mat[:,0].max(),house_mat[:,1].max()])\n",
    "plt.xticks(fontsize=25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3 对属性进行标准化( Z-Score 标准化 )\n",
    "$$\n",
    "x_{i}:=\\frac{x_{i}-\\mu_{i}}{s_{i}}\n",
    "$$\n",
    "\n",
    "μ= mean(x)\n",
    "\n",
    "s = max(x)-min(x)\n",
    "\n",
    "#### 标准化\n",
    "\n",
    "**标准化**是数据预处理中的一种技术，目的是将数据转换到一个统一的尺度上，使得不同特征（属性）的值在相同的范围内，通常为了让算法更有效地处理这些数据。标准化常见于机器学习和统计学中，特别是在特征值有显著不同的情况下。\n",
    "\n",
    "###### 标准化的目的\n",
    "\n",
    "1. **统一量纲**：不同特征可能有不同的量纲（如米、千克、秒等），标准化可以消除不同特征量纲的影响，使它们具有相同的尺度。\n",
    "   \n",
    "2. **加速模型收敛**：在一些机器学习算法中（如梯度下降），标准化后的数据能够让优化算法更快收敛，提高训练速度。\n",
    "   \n",
    "3. **增强模型性能**：标准化可以提升模型的表现，尤其在特征之间尺度差异较大的时候，避免某些特征主导整个模型。\n",
    "\n",
    "#### 常见的标准化方法\n",
    "\n",
    "##### 1. Z-Score 标准化\n",
    "将数据转化为均值为 0、标准差为 1 的正态分布。Z-Score 标准化适用于数据呈现正态分布的情况。\n",
    "   \n",
    "公式：\n",
    "$$\n",
    "x_{i} := \\frac{x_{i} - \\mu}{\\sigma}\n",
    "$$\n",
    "\n",
    "- $x_{i}$：原始数据\n",
    "- $\\mu$：特征的均值\n",
    "- $\\sigma$：特征的标准差\n",
    "\n",
    "##### 2. 最小-最大归一化\n",
    "将数据缩放到一个特定的范围（通常是 [0, 1]）。这种方法适用于数据分布比较平滑且无明显异常值的情况。\n",
    "\n",
    "公式：\n",
    "$$\n",
    "x_{i} := \\frac{x_{i} - \\min(x)}{\\max(x) - \\min(x)}\n",
    "$$\n",
    "\n",
    "- $\\min(x)$：特征的最小值\n",
    "- $\\max(x)$：特征的最大值\n",
    "\n",
    "##### 3. 最大绝对值标准化\n",
    "将数据按特征的绝对值最大值进行缩放，使得特征范围在 [-1, 1] 之间，常用于处理稀疏数据。\n",
    "\n",
    "公式：\n",
    "$$\n",
    "x_{i} := \\frac{x_{i}}{\\max(|x|)}\n",
    "$$\n",
    "\n",
    "##### 4. 单位向量标准化\n",
    "将数据标准化为单位向量，保证数据的范数为 1，常用于高维数据处理，如文本数据。\n",
    "\n",
    "公式：\n",
    "$$\n",
    "x_{i} := \\frac{x_{i}}{\\|x\\|}\n",
    "$$\n",
    "- $\\|x\\|$ 是特征向量的 L2 范数（即平方和的平方根）。\n",
    "\n",
    "##### 5. Robust 标准化\n",
    "对数据的中位数进行标准化，不受异常值的影响，适合含有离群点的数据集。\n",
    "\n",
    "公式：\n",
    "$$\n",
    "x_{i} := \\frac{x_{i} - \\text{median}(x)}{\\text{IQR}(x)}\n",
    "$$\n",
    "\n",
    "- $\\text{median}(x)$：特征的中位数\n",
    "- $\\text{IQR}(x)$：四分位距，即第 75 百分位与第 25 百分位的差值。\n",
    "\n",
    "#### 标准化的好处\n",
    "\n",
    "1. **提高模型表现**：许多机器学习算法，如支持向量机（SVM）、k-近邻（k-NN）、神经网络等，对特征的尺度非常敏感。标准化有助于提升这些模型的精度和收敛速度。\n",
    "\n",
    "2. **避免特征主导**：当某些特征的数值范围远大于其他特征时，这些特征会对模型产生过大的影响。标准化可以使每个特征的贡献相等，避免某些特征在优化过程中主导模型。\n",
    "\n",
    "3. **稳定梯度下降**：在使用梯度下降法进行优化时，标准化可以避免某些特征值过大导致梯度爆炸问题，使得模型更稳定。\n",
    "\n",
    "#### 标准化的场景\n",
    "\n",
    "- **回归分析**：在回归模型中，标准化能够使回归系数的估计更加稳定，尤其在特征之间的尺度差异较大时。\n",
    "  \n",
    "- **距离度量算法**：如 k-近邻（k-NN）和 k-均值（k-means）等依赖于距离计算的算法，特征值的尺度对距离计算结果有显著影响，标准化可以避免特征值大者主导距离计算结果。\n",
    "\n",
    "- **神经网络**：在神经网络中，标准化能够加快收敛速度，特别是对于深度神经网络。\n",
    "\n",
    "#### 总结\n",
    "标准化是机器学习和数据预处理中的一个重要步骤，它通过将不同特征值缩放到相同的范围，使算法在处理数据时更有效、更准确。根据数据的分布情况和模型的需求，可以选择不同的标准化方法，如 Z-Score 标准化、最小-最大归一化等。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "num = len(house_mat)\n",
    "x0 = np.ones(num) # 生成一行全1的数组作为x0\n",
    "x1 = (house_mat[:,0] - house_mat[:,0].mean())/(house_mat[:,0].max() - house_mat[:,0].min())           #对房间面积进行标准化\n",
    "x2 = (house_mat[:,1] - house_mat[:,1].mean())/(house_mat[:,1].max() - house_mat[:,1].min())           #对房间数进行标准化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.stack((x0,x1,x2), axis = 1)\n",
    "Y = label_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('X:',\n",
       " array([[ 1.        ,  0.46675444,  0.53125   ],\n",
       "        [ 1.        ,  0.09951723,  0.03125   ],\n",
       "        [ 1.        ,  0.05014264,  0.03125   ],\n",
       "        [ 1.        ,  0.31698486,  0.53125   ],\n",
       "        [ 1.        , -0.17807768, -0.46875   ],\n",
       "        [ 1.        ,  0.03917051,  0.03125   ],\n",
       "        [ 1.        ,  0.31347378,  0.53125   ],\n",
       "        [ 1.        ,  0.20375247,  0.03125   ],\n",
       "        [ 1.        ,  0.12354619,  0.03125   ],\n",
       "        [ 1.        ,  0.46763221,  0.53125   ],\n",
       "        [ 1.        , -0.45731841, -0.46875   ],\n",
       "        [ 1.        , -0.53236779, -0.46875   ],\n",
       "        [ 1.        , -0.30096555, -0.46875   ],\n",
       "        [ 1.        , -0.35560676, -0.46875   ],\n",
       "        [ 1.        , -0.15547509,  0.03125   ],\n",
       "        [ 1.        , -0.10116305,  0.03125   ]]),\n",
       " 'Y:',\n",
       " array([[145.  ],\n",
       "        [110.  ],\n",
       "        [ 93.  ],\n",
       "        [116.  ],\n",
       "        [ 65.32],\n",
       "        [104.  ],\n",
       "        [118.  ],\n",
       "        [ 91.  ],\n",
       "        [ 62.  ],\n",
       "        [133.  ],\n",
       "        [ 51.  ],\n",
       "        [ 45.  ],\n",
       "        [ 75.5 ],\n",
       "        [ 69.5 ],\n",
       "        [ 75.69],\n",
       "        [ 95.3 ]]))"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"X:\", X,\"Y:\", Y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.4 重新绘制面积和房间数属性范围的关系图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.bar(['面积','房间数'],[X[:,1].min(),X[:,2].min()])\n",
    "plt.bar(['面积','房间数'],[X[:,1].max(),X[:,2].max()])\n",
    "plt.xticks(fontsize=25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 训练算法\n",
    "\n",
    "求得回归系数θ\n",
    "\n",
    "$$\n",
    "h_{\\theta}(x)=\\left[\\begin{array}{llll}\n",
    "\\theta_{0} & \\theta_{1}  & \\theta_{2}\n",
    "\\end{array}\\right]\\left[\\begin{array}{c}\n",
    "x_{0} \\\\\n",
    "x_{1} \\\\\n",
    "x_{2}\n",
    "\\end{array}\\right]=\\theta^{T} x\n",
    "$$\n",
    "\n",
    "注：对于线性回归模型而言，一般使用该假设函数\n",
    "\n",
    "\n",
    "除了线性回归模型使用的线性假设函数 $\n",
    "h_{\\theta}(x)=\\left[\\begin{array}{llll}\n",
    "\\theta_{0} & \\theta_{1}  & \\theta_{2}\n",
    "\\end{array}\\right]\\left[\\begin{array}{c}\n",
    "x_{0} \\\\\n",
    "x_{1} \\\\\n",
    "x_{2}\n",
    "\\end{array}\\right]=\\theta^{T} x\n",
    "$，其他模型通常会根据数据的性质和任务的复杂度选择不同的假设函数。以下是几种常见模型及其假设函数。\n",
    "除了线性回归模型使用的线性假设函数 $h_{\\theta}(x) = \\theta^T x $，其他模型通常会根据数据的性质和任务的复杂度选择不同的假设函数。以下是几种常见模型及其假设函数：\n",
    "\n",
    "#### 1. **多项式回归**\n",
    "   - **假设函数**：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 + \\theta_3 x^3 + \\cdots + \\theta_n x^n\n",
    "     $$\n",
    "   - **说明**：\n",
    "     多项式回归扩展了线性回归，通过引入特征的高次项来拟合复杂的非线性关系。假设函数仍然是线性的，但它处理的是多项式特征。\n",
    "\n",
    "#### 2. **逻辑回归（Logistic Regression）**\n",
    "   - **假设函数**：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\frac{1}{1 + e^{-\\theta^T x}}\n",
    "     $$\n",
    "   - **说明**：\n",
    "     逻辑回归用于二分类任务，假设函数是一个**S型函数**（Sigmoid函数），它将线性组合的结果映射到 $[0, 1] $ 的概率空间上。输出表示输入样本属于某个类别的概率。\n",
    "\n",
    "#### 3. **支持向量机（SVM）**\n",
    "   - **假设函数**：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\text{sign}(\\theta^T x + b)\n",
    "     $$\n",
    "   - **说明**：\n",
    "     支持向量机主要用于分类任务，其假设函数通过计算输入特征与超平面的距离来做出分类决策。如果结果大于 0，则属于正类；小于 0，则属于负类。\n",
    "   \n",
    "   - **核函数**：\n",
    "     为了处理非线性分类问题，SVM 可以引入**核函数** $K(x, z) $，如高斯核（RBF）或多项式核，将输入特征映射到高维空间：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\text{sign}( \\sum_i \\alpha_i y_i K(x_i, x) + b)\n",
    "     $$\n",
    "\n",
    "#### 4. **神经网络（Neural Networks）**\n",
    "   - **假设函数**：\n",
    "     $$\n",
    "     h_{\\theta}(x) = f(W^{[2]} f(W^{[1]} x + b^{[1]}) + b^{[2]})\n",
    "     $$\n",
    "   - **说明**：\n",
    "     神经网络的假设函数是一个嵌套的函数，由多个**线性变换**和**非线性激活函数**（如 ReLU、Sigmoid、Tanh）组成。每一层通过一个线性变换（权重矩阵 $W $ 和偏置项 $b $），然后经过激活函数 $f $，从而能够拟合高度复杂的非线性关系。\n",
    "   - **激活函数**：\n",
    "     - Sigmoid： $f(z) = \\frac{1}{1 + e^{-z}} $\n",
    "     - Tanh：$f(z) = \\frac{e^z - e^{-z}}{e^z + e^{-z}} $\n",
    "     - ReLU：$f(z) = \\max(0, z) $\n",
    "\n",
    "#### 5. **决策树（Decision Trees）**\n",
    "   - **假设函数**：\n",
    "     决策树没有具体的数学假设函数，它通过一系列**条件判断**来拟合数据：\n",
    "     - 如果某个特征满足某个条件，则选择一个分支，否则选择另一个分支。\n",
    "   - **说明**：\n",
    "     决策树模型在输入特征空间中递归地进行分割，每个分割对应一个条件判断，最终叶子节点上的值即为预测值（回归）或分类结果（分类）。\n",
    "\n",
    "#### 6. **随机森林（Random Forest）**\n",
    "   - **假设函数**：\n",
    "     随机森林是多个决策树的集成，假设函数是各个决策树的预测结果的平均值（回归）或投票结果（分类）：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\frac{1}{n} \\sum_{i=1}^{n} h_{\\theta}^{(i)}(x)\n",
    "     $$\n",
    "   - **说明**：\n",
    "     随机森林通过聚合多个决策树的预测结果来提高模型的鲁棒性，减少过拟合。\n",
    "\n",
    "#### 7. **梯度提升决策树（Gradient Boosting Decision Trees, GBDT）**\n",
    "   - **假设函数**：\n",
    "     GBDT 使用一系列弱学习器（通常是决策树），每个树依次修正前一个树的错误预测，形成一个加法模型：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\sum_{i=1}^{n} \\alpha_i h_{\\theta}^{(i)}(x)\n",
    "     $$\n",
    "   - **说明**：\n",
    "     这个模型的假设函数是多个基学习器的加权和，每个基学习器尝试修正之前的误差。\n",
    "\n",
    "#### 8. **k-近邻算法（k-Nearest Neighbors, k-NN）**\n",
    "   - **假设函数**：\n",
    "     k-NN 没有显式的假设函数，它通过计算输入点 $x $ 与训练集中的所有点之间的距离，选取最近的 $k $ 个邻居的平均值（回归）或投票结果（分类）：\n",
    "     $$\n",
    "     h_{\\theta}(x) = \\frac{1}{k} \\sum_{i \\in \\text{k-NN}} y_i\n",
    "     $$\n",
    "   - **说明**：\n",
    "     这种方法通过计算输入数据与邻居的相似性来预测，没有参数化的假设函数，属于懒惰学习。\n",
    "\n",
    "#### 9. **贝叶斯模型（Bayesian Models）**\n",
    "   - **假设函数**：\n",
    "     贝叶斯模型基于条件概率的假设函数，通过贝叶斯定理计算后验概率：\n",
    "     $$\n",
    "     P(y|x) = \\frac{P(x|y)P(y)}{P(x)}\n",
    "     $$\n",
    "   - **说明**：\n",
    "     贝叶斯模型假设数据生成过程服从某种概率分布，并根据先验知识和观测数据进行预测。\n",
    "\n",
    "#### 总结\n",
    "\n",
    "不同模型使用不同的假设函数，选择什么样的假设函数通常取决于以下几个因素：\n",
    "- **任务的性质**：是回归、分类还是无监督学习？\n",
    "- **数据的特性**：线性还是非线性？特征之间的关系是否复杂？\n",
    "- **计算复杂度**：一些模型（如神经网络和树模型）能够处理复杂的非线性关系，但计算成本较高。\n",
    "- **模型的可解释性**：线性回归和逻辑回归容易解释，而神经网络等复杂模型可解释性较差。\n",
    "\n",
    "总的来说，模型的假设函数是用来描述输入和输出之间的映射关系，不同的模型使用不同的假设函数来捕捉这种关系的特点和复杂度。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1 使用梯度下降法"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\theta_{j}:=\\theta_{j}-\\alpha \\frac{1}{m} \\sum_{i=1}^{m}\\left(h_{\\theta}\\left(x^{(i)}\\right)-y^{(i)}\\right) \\cdot x_{j}^{(i)} \\quad \\text { for } \\mathrm{j}:=0 \\ldots \\mathrm{n}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\text { 目标：使代价函数 } \\frac{1}{2m} \\sum_{i=1}^{m}\\left(y^{(i)}-\\hat{y}^{(i)}\\right)^{2} \\quad \\text { 尽可能小 }\n",
    "$$\n",
    "\n",
    "- **代价函数**：代价函数是衡量模型预测值与实际值之间差距的函数。它的作用是量化模型的预测误差。常见的代价函数有均方误差（MSE）和交叉熵损失等。可以简单的认为，代价函数的最小值即为模型参数θ的**最佳值**。\n",
    "\n",
    "#### 如何确定一个模型的代价函数？\n",
    "确定一个模型的代价函数（Cost Function），主要取决于模型的类型、任务的目标（如回归或分类）以及评价模型性能的方式。代价函数用于量化模型预测值与实际值之间的差距，因此其选择非常关键。\n",
    "\n",
    "##### 1. **模型任务类型**\n",
    "不同的任务类型往往使用不同的代价函数：\n",
    "\n",
    "- **回归问题**：预测连续值，如房价、温度等。\n",
    "- **分类问题**：预测离散的类别，如识别图片中的动物是猫还是狗。\n",
    "\n",
    "##### 2. **常见的代价函数**\n",
    "\n",
    "##### **1. 回归问题**\n",
    "在回归任务中，目标是最小化预测值与实际值之间的差距。常用的代价函数有：\n",
    "\n",
    "**(a) 均方误差（MSE，Mean Squared Error）**：\n",
    "- MSE 是回归问题中最常用的代价函数，计算的是预测值和实际值之间的差值的平方平均值。\n",
    "$$\n",
    "J(\\theta) = \\frac{1}{m} \\sum_{i=1}^m (h_\\theta(x^{(i)}) - y^{(i)})^2\n",
    "$$\n",
    "其中：\n",
    "- $m$ 是样本数。\n",
    "- $h_\\theta(x^{(i)})$ 是模型预测值。\n",
    "- $y^{(i)}$ 是真实值。\n",
    "\n",
    "**(b) 平均绝对误差（MAE，Mean Absolute Error）**：\n",
    "- MAE 计算的是预测值和实际值之间差值的绝对值的平均值。\n",
    "$$\n",
    "J(\\theta) = \\frac{1}{m} \\sum_{i=1}^m |h_\\theta(x^{(i)}) - y^{(i)}|\n",
    "$$\n",
    "MAE 更加鲁棒，特别是对异常值（outliers）的处理，它不像 MSE 那样会因为少数的异常值受到过大的影响。\n",
    "\n",
    "##### **2. 分类问题**\n",
    "在分类任务中，目标是预测样本属于某个类别的概率。常见的代价函数有：\n",
    "\n",
    "**(a) 交叉熵损失（Cross-Entropy Loss）**：\n",
    "- 交叉熵损失用于二元分类或多元分类问题。它衡量模型预测的概率分布与真实分布之间的差异。对于二元分类，交叉熵损失的形式是：\n",
    "$$\n",
    "J(\\theta) = -\\frac{1}{m} \\sum_{i=1}^m \\left( y^{(i)} \\log(h_\\theta(x^{(i)})) + (1 - y^{(i)}) \\log(1 - h_\\theta(x^{(i)})) \\right)\n",
    "$$\n",
    "其中：\n",
    "- $h_\\theta(x^{(i)})$ 是预测为正类别的概率。\n",
    "- $y^{(i)}$ 是实际的类别标签，取 0 或 1。\n",
    "\n",
    "**(b) Softmax 损失（用于多分类问题）**：\n",
    "- Softmax 损失是交叉熵损失的扩展，用于多分类任务。对于 $K$ 类的分类问题，损失函数为：\n",
    "$$\n",
    "J(\\theta) = -\\frac{1}{m} \\sum_{i=1}^m \\sum_{k=1}^K y_k^{(i)} \\log(h_\\theta(x^{(i)})_k)\n",
    "$$\n",
    "其中 $h_\\theta(x^{(i)})_k$ 是预测属于第 $k$ 类的概率，$y_k^{(i)}$ 是实际的标签（one-hot 编码形式）。\n",
    "\n",
    "##### **3. 其他常见的代价函数**\n",
    "根据具体问题，其他常用的代价函数包括：\n",
    "\n",
    "**(a) Huber 损失**：\n",
    "- 结合了 MSE 和 MAE 的优点，适用于处理包含少量异常值的回归问题。当误差小于某个阈值时，使用平方误差；当误差较大时，使用绝对误差：\n",
    "$$\n",
    "J(\\theta) = \n",
    "\\begin{cases} \n",
    "\\frac{1}{2}(h_\\theta(x^{(i)}) - y^{(i)})^2 & \\text{if } |h_\\theta(x^{(i)}) - y^{(i)}| \\leq \\delta \\\\\n",
    "\\delta |h_\\theta(x^{(i)}) - y^{(i)}| - \\frac{1}{2} \\delta^2 & \\text{otherwise}\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "**(b) Hinge 损失**：\n",
    "- 常用于支持向量机（SVM）等二分类模型。对于一个样本 $i$，Hinge 损失为：\n",
    "$$\n",
    "J(\\theta) = \\max(0, 1 - y^{(i)} h_\\theta(x^{(i)}))\n",
    "$$\n",
    "其中 $y^{(i)} $ 是类别标签，取值为 +1 或 -1。\n",
    "\n",
    "##### 3. 确定代价函数的步骤\n",
    "\n",
    "##### **1. 根据任务类型选择合适的代价函数**\n",
    "- **回归问题**：常使用均方误差（MSE）、平均绝对误差（MAE）等。\n",
    "- **分类问题**：常使用交叉熵损失（Cross-Entropy Loss）、Softmax 损失、Hinge 损失等。\n",
    "\n",
    "##### **2. 考虑数据的特点**\n",
    "- **是否有异常值**：如果数据中有很多异常值，可能需要使用更加鲁棒的代价函数（如 MAE、Huber 损失）。\n",
    "- **输出的性质**：如果输出是概率值，交叉熵损失较为合适。如果是连续值，MSE 通常是首选。\n",
    "\n",
    "##### **3. 考虑模型的需求**\n",
    "- 不同的模型可能需要不同的代价函数。例如，支持向量机（SVM）通常使用 Hinge 损失，而神经网络中的分类模型常用交叉熵损失。\n",
    "\n",
    "##### 总结\n",
    "确定模型的代价函数通常基于以下几个因素：\n",
    "1. **任务类型**：是回归还是分类问题。\n",
    "2. **数据的特点**：是否有异常值，输出值的性质等。\n",
    "3. **模型需求**：不同模型适用的代价函数不同。\n",
    "\n",
    "最终，通过选择合适的代价函数，可以为模型提供一个优化的目标，使得模型能够更好地拟合训练数据，并在测试数据上有良好的泛化能力。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1.1 设置α和迭代次数\n",
    "\n",
    "α的取值判断\n",
    "* 调试梯度下降。绘制一个在x轴上具有迭代次数的图。现在在梯度下降的迭代次数上绘制代价函数J（θ）。如果J（θ）增大，则可能需要减小α。\n",
    "\n",
    "* 自动收敛测试。如果在一次迭代中J（θ）的减小量小于E，则声明收敛，其中E是一些小值，例如$10^{−3}$ \n",
    " 。但是，实际上很难选择此阈值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn_rate = 0.1 # 学习率α\n",
    "iter = 500  # 迭代次数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1.2 初始化θ向量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.82418808],\n",
       "       [0.479966  ],\n",
       "       [1.17346801]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(666)\n",
    "W = np.random.randn(3,1) # 初始化θ向量为全随机值\n",
    "W"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1.3 执行梯度下降"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用梯度下降算法来计算代价函数的最小值是机器学习模型优化过程中的一个关键步骤。梯度下降算法通过迭代更新模型参数，逐渐减少代价函数的值，直至找到最优的参数使代价函数最小化。以下是梯度下降算法的基本步骤及如何利用它来找到代价函数的最小值：\n",
    "\n",
    "### 1. 定义代价函数（Cost Function）\n",
    "\n",
    "首先，定义代价函数 $ J(\\theta) $，这是一个关于模型参数 $\\theta$ 的函数。代价函数衡量了模型预测值与实际值之间的误差。在回归问题中，常用的代价函数是均方误差（MSE）：\n",
    "\n",
    "$$\n",
    "J(\\theta) = \\frac{1}{2m} \\sum_{i=1}^m (h_\\theta(x^{(i)}) - y^{(i)})^2\n",
    "$$\n",
    "\n",
    "其中：\n",
    "- $ m $ 是样本数量。\n",
    "- $ h_\\theta(x^{(i)}) $ 是模型的预测值。\n",
    "- $ y^{(i)} $ 是实际值。\n",
    "\n",
    "### 2. 初始化参数\n",
    "\n",
    "随机初始化模型参数 $\\theta$（例如权重 $W$）。初始化的值可以是零、随机小值或其他方法。\n",
    "\n",
    "```python\n",
    "theta = np.random.randn(n_features)  # 随机初始化参数\n",
    "```\n",
    "\n",
    "### 3. 设置超参数\n",
    "\n",
    "选择合适的超参数，包括学习率 $\\alpha$ 和迭代次数 $iter$：\n",
    "\n",
    "- **学习率（Learning Rate）**：控制每次参数更新的步长大小。过大可能导致收敛不稳定，过小可能导致收敛速度很慢。\n",
    "- **迭代次数（Iterations）**：定义算法运行的次数。\n",
    "\n",
    "```python\n",
    "learn_rate = 0.01  # 学习率\n",
    "iterations = 1000  # 迭代次数\n",
    "```\n",
    "\n",
    "### 4. 实现梯度下降算法\n",
    "\n",
    "进行迭代更新，直到收敛或达到最大迭代次数。在每次迭代中，计算代价函数的梯度，并更新参数：\n",
    "\n",
    "```python\n",
    "for i in range(iterations):\n",
    "    # 计算预测值\n",
    "    h_theta = np.matmul(X, theta)\n",
    "    \n",
    "    # 计算误差\n",
    "    error = h_theta - y\n",
    "    \n",
    "    # 计算梯度\n",
    "    gradient = np.matmul(X.T, error) / m\n",
    "    \n",
    "    # 更新参数\n",
    "    theta -= learn_rate * gradient\n",
    "    \n",
    "    # 计算代价函数值\n",
    "    cost = np.mean(np.square(error)) / 2\n",
    "    mse.append(cost)  # 记录代价函数值\n",
    "```\n",
    "\n",
    "### 5. 检查收敛\n",
    "\n",
    "监控代价函数的值，如果代价函数值趋于稳定或变化非常小，可以认为算法已经收敛。可以设置一个阈值来判断是否停止迭代。\n",
    "\n",
    "### 6. 最终结果\n",
    "\n",
    "在迭代结束后，得到的参数 $\\theta$ 应该是使代价函数最小化的参数。可以使用这些参数进行模型的预测和分析。\n",
    "\n",
    "### 总结\n",
    "\n",
    "1. **定义代价函数**：衡量模型预测与实际值之间的误差。\n",
    "2. **初始化参数**：为模型参数 $\\theta$ 赋初值。\n",
    "3. **设置超参数**：选择合适的学习率和迭代次数。\n",
    "4. **梯度下降**：通过计算梯度并更新参数来逐步减少代价函数值。\n",
    "5. **监控收敛**：确保算法在收敛后停止迭代。\n",
    "6. **使用结果**：使用找到的最优参数进行模型预测。\n",
    "\n",
    "通过这些步骤，梯度下降算法可以有效地找到使代价函数最小化的参数，从而优化模型性能。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "np.matmul(X,Y) : X * Y\n",
    "\n",
    "np.transpose(X) : X 转置\n",
    "\n",
    "np.square(X) : 求X的平方"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "mse = []  #保存每一次θ更新后的代价函数\n",
    "for i in range(iter+1):\n",
    "    dJ_dw = np.matmul(np.transpose(X),np.matmul(X,W)-Y)    #求J对θ的偏导\n",
    "    W = W-learn_rate*dJ_dw                   #更新θ\n",
    "    \n",
    "    h_price = np.matmul(X,W)  #计算此时的预测值 h(θ)\n",
    "    COST = np.mean(np.square(Y-h_price))/2  #计算此时的代价函数J\n",
    "    mse.append(COST)    #保存此时的代价函数J\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1.4 结果可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Tk+Pf39TUxL333stZZ53FJZdcgt1u7/fzbNu2jRtvvJH333+f+++/n4suuojp06fz2Wef8fDDD3P//fezbNmyHq9tb2/n2WefZe7cuWRldfxe3nPPPdTX13PrrbeSkpLS7bqDBw8CnDCoOf718ba2Nn784x8zcuRIFixY0O/PLxKiY1KOBKRjRo2IiIiIiIj0ZmZ+BgDFZbURXYeIiIhIqFVUVPD//t//Y9y4cfz4xz/uNj/mvffe46WXXuLyyy8nNzeX7373u+zfv7/X+zU2NvL888+zdOlSpk+fzpYtW3j88ce5++67iYuL4+OPP+YXv/gFFRUVXHbZZSxcuJD333+/231WrlzJoUOH+OpXv+rf97vf/Y7f/OY33HDDDV2qbDpbs2YNANOmTet1jc3NzQC43W7AbKH28ccf8/3vf5+4uLgu5/rOiZbiBwU1scCInvI6ERERERGRaDWzIAOAz4824Ghui+xiRERERILM4/HwwgsvcMUVV1BQUMCjjz7K1Vdfzaeffsovf/nLLudecMEF7Nq1i7Vr13LWWWfxyCOPMG7cOO644w7/OWVlZdx1111ceOGFjBgxgiuvvJJ//vOfXH/99WzdupX//M//9J+bnJzM7bffzt69e7n99tvZuHEjZ511FsuXL8fpdAId4VFGRgZXXnklhw4d4oYbbuCWW27h/PPP59FHH+2yxjvvvJP58+czY8YMHnroIfLy8pg8eXKvn39Lizk/qLW1lauvvprf//73XHDBBdx6663dzvWtybeNNAU1MSRKwj8REREREZGolJ1ipyAzCYAtB2ojuxgRERGRIDMMg4qKCioqKvjtb3/LoUOHeOyxx5g0aVKv15xzzjn84x//YOPGjSxevLhL+FJQUEBTUxNr167ljDPO4He/+x0HDhxgxYoVjB07tsf7paWl8Ytf/IJPPvmE0047jaKiIn9btZycHH75y19y3333kZGRwUcffcQzzzzDNddcw0svvURiYmKXe82ePZt9+/aRkJDAtddey4svvojF0nuk0d7eDpjhy+WXX87ixYv561//itFDoYMvoPGFO5FmeKKltmcIq6urIz09HYfDQVpaWtif/5F/7uLXb33ONfMK+MkXey/9EhEREREJlkh/DyxDT7R8zXz7+WJeLDnEdy+YwG3njY/YOkRERCRwLS0tlJaWUlhYSEJCQqSXE5Oam5tpa2sb1Pdv7e3tWK3WHoMSn127dp1w7kwgPB7PCZ97sPr7dTeQ739VURMDfF9ritxEREREREROzDenpqS8NqLrEBERERkKEhMTB/0mG5vN1mdQEqqQBghJSBMqCmpigIH5BaecRkRERERE5MRmFQwDoLisJmqGx4qIiIjIyU1BTQxQRY2IiIiIiEj/TMlLI95moaapjf3HmiK9HBERERERBTWxoKOAS0mNiIiIiIjIicTbLEwdabbvKC6vifBqRERERESGeFBTVVVFYWEh+/bt63bs+9//PkuXLu2yb9u2bcyZM4dhw4Zx5513dilzX7duHZMnTyY7O5uHH3441EsPKlXUiIiIiIiI9N/MfLP9WUlZbWQXIiIiIiLCEA5qqqqqWLJkSY8hzZYtW/jd737Hr3/9a/8+p9PJ0qVLmT17Nh9//DHbt2/nqaeeAqCyspJly5Zx5ZVXsmHDBlatWsXatWvD9JkEzjcUSUGNiIiIiIhI32YVZABQXF4b0XWIiIiIiMAQDmqWL1/OVVdd1W2/2+3mG9/4Bt/5zncoKiry71+zZg0Oh4OHH36YcePGcf/99/PEE08AsGrVKkaOHMkPfvADxo8fz7333us/1hOn00ldXV2Xj2jgUeszERERERGRPvmCmu2H6mhpc0V2MSIiIiJy0huyQc2KFSu47bbbuu3//e9/z9atWxk7diwvvfQSra2tAGzevJl58+aRlJQEwPTp09m+fbv/2OLFi/2VKXPnzmXTpk29PvcDDzxAenq6/yM/Pz/Yn96AqPWZiIiIiIhI/43KSGR4qp12t4dtBx2RXo6IiIiInOSGbFBTWFjYbV9DQwP33XcfRUVF7N+/n0ceeYQFCxbQ3NxMXV1dl2sMw8BqtVJTU9PtWFpaGocOHer1ue+++24cDof/o7y8PLif3AAZeFufRXQVIiIiIiIiQ4NhGMzMzwCgRO3PRERERCTCbJFeQDD99a9/pbGxkbVr15KdnU17ezvTpk3jmWeewWazYbfbu5yfkJBAU1NTt2O+/b2x2+3d7hVJqqgREREREREZmFkFGfxz+xGKy2ojvRQRERER8Tp48CCvvfYa119//aCud7vdAFgsQ6tGZWittg8HDhxg3rx5ZGdnA2Cz2Zg+fTq7d+8mMzOTysrKLufX19cTHx/f7Zhv/1BhRHoBIiIiIiIiQ8ys/GEAFJfVRHglIiIiIuHR0NBAU1MTLlfPM/ra29tpaGjwjxPxeDw899xz/vBjoB5//HGWL19Oc3Nzv6+5+eabueGGG/joo48G9Zxr166lqKiIxx57rNuxV199lcWLF/PWW28N6t6hFFNBzejRo7v9oe/fv59Ro0YxZ84cNmzY4N9fWlqK0+kkMzOz27Hi4mJGjRoVtnUHi0fNz0RERERERPpl+uh0LAYccrRQ4WiJ9HJEREREAvaTn/yE0aNHU1RUxKRJk7p8/PGPf+SLX/wiycnJ2Gw2DMPo9hEXF0dqaiqrV68GYPXq1Vx11VUsXrzYPyrk/vvv54c//GG3jwcffLDbej799FP++Mc/EhcX1+/P4Wtf+xoAf/vb3wb1e7BmzRr2799Pbm5ut2MrV67knXfeYcuWLYO6dyjFVOuzSy+9lFtvvZXf//73LFmyhL/+9a9s3ryZP//5z+Tl5VFXV8eTTz7J17/+de6//37OP/98rFYry5Yt45ZbbuHNN99k0aJFPPTQQ1x44YWR/nT6zdf6TDmNiIiIiIhI/yTbbUzMTWPH4TpKymu4KD0v0ksSERERCcgVV1zBaaedht1uJz4+ntbWVq666ircbjdTpkzh6aefpr293T/WIy8vjxtvvJGf/OQnALS1tdHS0kJWVhYAV111FUePHuX73/8+c+bMYcuWLfzyl78kLi6uSxBy4MAB4uPjueuuu2hra8PtdmO32/0Bjc3WPYYYN24ce/fu7fVzeeCBB3jggQe67c/JyaGioqLHa9rb2/njH//I+PHj+eIXv9jl2JYtW/j73/9OUlISP/vZz7j22mv9n2c0iKmKmqysLF599VWefvppJkyYwK9//Wv+9Kc/kZ+fj81mY+XKlXzrW98iOzubF198kZ/97GcAZGdn88gjj3DJJZeQk5PDzp07ueeeeyL82fSf4W1+ppxGREREREQGoqqqisLCQvbt29fj8YsuuoinnnrK/+t169YxefJksrOzefjhh8OzyBCamZ8BQHF5bUTXISIiIhIMkydP5pJLLmH27NksXLiQNWvWUF9fz5o1a5g2bRqjRo1izJgx5Obm4vEOPJ89ezbZ2dlkZ2eTl5dHYWEhaWlpABiGwXe+8x3WrFnDf/3Xf5GVlYXdbuemm26ipKTE//Fv//Zv/lDm61//OqNHj+5zrXFxccyZM4cdO3b0++OLX/wiCQkJvd7z73//OwcOHOC2227DMLoODLn99ttJTk5m48aNJCQkcM0119DW1jbY3+qgG/IVNb4vKJ+zzjqrSxuzzpYtW8aePXvYtGkT8+bN65KY3XTTTVx44YV89tlnLFy4kJSUlJCuO5h8X3PH/16IiIiIiIj0pqqqiiVLlvQa0qxatYrXX3+d5cuXA1BZWcmyZcu4/fbbufLKK1m+fDmzZs1i8eLFYVx1cM0qyOC5D8soLquN9FJEREREgmL37t2cccYZXH/99fzqV7/if//3fzn99NO7nff5558DZrjTl/POO4/zzjsPAIvFrP3Yt28f69evZ8GCBQD+YCQxMZHExMQ+7xkfH09SUhKTJk3q3ycGpKen+6uBeuJ7I9FXvvKVLvsff/xx3nzzTX79618zdepUVq9ezeLFi1m+fDnPP//8gFqzhUpMVdT0R25uLpdeemmPZU2FhYVcfPHFQyqk6UwxjYiIiIiI9Nfy5cu56qqrejxWXV3N7bffzsSJE/37Vq1axciRI/nBD37A+PHjuffee3niiSd6vb/T6aSurq7LR7Q5rSADgC0Haml3DW5IroiIiEg0GTNmDF/4whf4+c9/zsSJE7n++uu7HPfNp1m0aBEACxcu7DKnxjcjBuCDDz7wz6Y53v79+7n22mt59dVXu+y3Wq3+MOdELBYLbreblpaWfn+4XK5eixX+/Oc/+ws4kpOT/fvffPNNbr31Vi6//HJuu+02AObPn8/TTz/N3/72NxYuXEhZWVmf6w21ky6oiUW+tFIFNSIiIiIi0l8rVqzw/7B6vNtvv50vfelLzJs3z79v8+bNLF682P/zx9y5c9m0aVOv93/ggQdIT0/3f+Tn5wf3EwiCouwUUhNstLS5+ayiPtLLERERkaHAcRBK3zW3USguLo5Vq1Zx9dVXs2/fPkpLS7sct9vtfP3rX++xtVh2dra/tVhLSwv//u//zuzZs/nggw+6PU9qaioAmZmZg1qnxWJh/fr1/gqc/nw8++yzNDc3d7tXS0sLd911V7f9f/nLX1i6dCnTpk3r0s4XzDctrVy5kk2bNjF9+nQefPBBmpqaBvW5BIOCmhjg67annEZERERERPqrsLCwx/1r167lrbfe4qGHHuqyv66urss1aWlpvb7DEuDuu+/G4XD4P8rLy4Oz8CCyWAz/nJoSzakRERGJLR4PtDYG9+PDFfCrqfD0UnP74Yrg3j/Ad+J/9NFHFBcXs2vXLr7//e/zm9/8BqfTyWeffcZnn31Gc3MzdrudzMxMJk2aRGVlJX//+9+x2+1MmjQJq9Xqby2WkJDAc889h8fjYfHixbz44otdnsv35p3BdqcyDIMzzjiD0tLSbh9PPvkkl156Kbt27ep27P333+92r29+85vs3buXhQsXAtDW1sZ3v/td/v3f/51Jkybxxhtv+IOlzq677jr+8Y9/EB8fz913380zzzwzqM8lGIb8jBrRjBoREREREQmOlpYWbrzxRh577LFuP8zabLYuPcETEhJO+K5Du91+wh7i0WJWfgbrP6+iuKyWa+aNifRyREREJFjamuD+kaG7v8cNr95hfgTLfx+C+OS+z+vFlVdeyZ49e3o9Xl5e3qUt2YYNG7j77ru59NJL/ft8AQzAggULWLt2LRdeeCHZ2dld7uU7z1eBM1Ctra2kpqYyduzYbsd2797NK6+8wnXXXcfll19+wvusWrWKJ598kgsuuIAvfOELrF+/HpvNRnNzM0uXLuXZZ5/lK1/5Cvv27aOkpMR/3U9/+lPuueceSkpK+PTTT/nTn/7EjTfeOKjPJRgU1MQAVdSIiIiIiEgw/PjHP2bOnDldflj3yczMpLKy0v/r+vp64uPjw7m8kJhVMAyA4vKaCK9EREREJDCffPIJ8fHxJCQksGDBAjIyMvjHP/7Bddddx1tvvcXo0aO7nN/S0gLAuHHjer3n5MmT2blzJ4mJiV3219bWAnTb31+tra0cPnyYlStXdjvmC5N+9atfUV1d7d/v8XhobW2ltbWV8847j+nTp3PZZZfxla98hR//+Mf8+c9/BswQ6Te/+Q2GYWCxWGhubsblcnV5Dt+6ExMTGT58OLfccsugPo9gUVATA/wpp5IaEREREREJwOrVq6msrCQjIwOApqYm/vSnP/Hhhx8yZ84cVq9e7T+3uLiYUaNGRWilweNrfba3shFHUxvpSXGRXZCIiIgER1ySWaESLHWH4LdzzUoaH8MKt2yEtCBV7sQlBXR5Wlpaj/vXr1/PggULuu1vbm4mNTWVpKQTP291dTW1tbWceuqptLa2AlBRUQFAeno6YLYbG4jGxkYqKyu7zJZxOp00NDSQnp5OVlYW27dv73Lc4/HgdDppbW3lscceY/r06aSkpPCHP/yh2/2tVqv/cVtbGyNHdv0zioszv+ez2aIjIomOVUhAOnIaJTUiIiIiIjJ469evp7293f/rO+64g3nz5vG1r30NgFtuuYU333yTRYsW8dBDD3HhhRdGaKXBMyw5nrFZSew71kTJgVoWTRge6SWJiIhIMBhGQG3EuskeD0t/DS//F3hcZkiz9Ffm/ij3zjvv+AOJzuMzqqqqyM3N7XKu2+3meP/3f//HAw88wMaNG/1Bzb59+wD8AYjT6RzQmiorK7n22mtZsWKFf9///u//ctNNN/HWW28xe/bsAd3vRBoaGpg8eXKXfb7ih86t4CJJQU0M8Lc+U04jIiIiIiIBOL4dRkpKCtnZ2f6e5I888giXXHIJKSkpZGRk8NRTT0VglcE3q2AY+441UVxWo6BGREREenfatTDuPKjeC5lFkD40qos7V0F3rnzZs2cPhYWFXc49PnBxuVw89dRT5OXlMXnyZC677DKmTp3K73//e7Kzs8nKyuK8887zV2S7XK4ub/zpydGjR2ltbSU/P7/bfoD333+fzz//vMdrc3JyWLx48Yk/4ePU1tYyfHh0f4+noCYWdBrwJCIiIiIiMhCeE7zj6/gg5qabbuLCCy/ks88+Y+HChaSkpIR4deExqyCDvxUfpLisNtJLERERkWiXPmrIBDQ9aW5uBswZMRs3buQb3/iG/1h6enqXlmEAf/nLX9i7dy8rVqzAZrPx9NNP09jYyDXXXMMll1zC9u3bufDCC/n3f/93wJx743uO3hQXFwMwderULvs3b94MwG233dbrtVdfffWAghqn00lpaWm3NyRFGwU1MUQVNSIiIiIiEmqFhYXd3nk51M3KHwZASXktbrcHi0VvhhMREZHYVFpaSmpqKn/9619pamriggsu4PXXX+fcc89l586dXc51uVz85Cc/YcyYMXz1q1/173/mmWdwOp2cddZZnHHGGZxxxhm89tpr2Gw2fvSjH/Hd7373hGt4++23MQyDRYsW+fc5HA7eeOMNrrjiih6rtisqKhg/fjwTJkwY0Of7+uuv097ezowZMwZ0XbhFRwM2CYi/9Zlm1IiIiIiIiAzYpLxU7DYLjuY2So81Rno5IiIiIiEzevRoDMPg3nvvZcSIEUyfPp0vfelLLFmyhIaGhi7nrlixgq1bt/K9732PuLg4ABobG7n//vspKCjgW9/6FrfccgtvvfUW99xzDwBFRUXMmjWr1+dvb2/n2WefZe7cuWRlZfn333PPPdTX13PrrbeSkpLS7ePgwYMAJwxqjq8Ub2tr48c//jEjR45kwYIFA/uNCjMFNTHA1/lMFTUiIiIiIiIDF2e1MG1UOgAlan8mIiIiMeDo0aMYPYzMqK+v54orruDzzz/n8ccfZ/To0fz+979n3bp1LF68mKqqKsCcX/O9732PYcOG8bWvfc1//Xe/+13Ky8t54IEHsNvt3H///SxcuJCHHnqIdevWdXmuY8eOdXv+lStXcujQoS4VOr/73e/4zW9+ww033NClyqazNWvWADBt2rReP2dfyzW32w2YLdQ+/vhjvv/97/uDJh/fOSdqAxxOCmpigOGtqYmOLykREREREZGhZ1ZBBgDF5TWRXYiIiIjIILW2tlJQUEBmZiaff/45BQUFXY6vXbuW0047jbfffptHH32Uyy67DIBrr72WV199lU8//ZRFixZRUVGBxWJh5syZXH/99SQlJQHwP//zPzz++OOcd955XHnllQBYLBZ+//vfY7PZeP311wFYvXo148aN4+mnnyY/P9///BUVFfy///f/yMjI4Morr+TQoUPccMMN3HLLLZx//vk8+uijXdZ75513Mn/+fGbMmMFDDz1EXl4ekydP7vXzb2lp8f8+XH311fz+97/nggsu4NZbb+12rtPp7LKNNAU1MUAVNSIiIiIiIoGZVWDOqSlWRY2IiIgMUfHx8cyePRubzcYXv/hF7rrrLv+x//7v/+bcc8+lubmZV155pVt4ce655/KXv/yFXbt2sWLFCgoLC1m7di3//d//7T/n1FNP5bzzzuO5557rUq0zZcoUNmzYwP333w/A+eefj8fj4ZprruHFF1/0n5eTk8Mvf/lL7rvvPjIyMvjoo4945plnuOaaa3jppZdITEzssqbZs2ezb98+EhISuPbaa3nxxRexWHqPNNrb2wEzfLn88stZvHgxf/3rX3usLPIFNL5wJ9IMT7TU9gxhdXV1pKen43A4SEtLC/vzP/9hGXf9dSvnTx7Byq/OCfvzi4iIiMjJJ9LfA8vQE+1fM4cdzZz5wNtYLQbbfnghifHWSC9JRERE+tDS0kJpaSmFhYUkJCREejlRrb29nf/7v/9j+fLlJ/xe7IMPPmDevHlhW9euXbtOOHcmEB6Pp8eQJlD9/bobyPe/qqiJAaqoERERERERCUxeeiI5aXZcbg9bDzoivRwRERGRoLLZbHzjG9/oMzAIZ0gDhCykAUIS0oSKgpoYoBk1IiIiIiIigZuV72t/pjk1IiIiIhI+Cmpigb+iRlGNiIiIiIjIYM0qyAA0p0ZEREREwktBTQzwFXApphERERERERm8WQVmRc0nZTV6I5yIiIiIhI2Cmhjg67WnnyNEREREREQGb9qodKwWg6P1Tg47WiK9HBEREeknvcFCwikUX28KamKAKmpEREREREQClxhvZVJuKgAl5bWRXYyIiIj0yWq1AtDW1hbhlcjJxPf15vv6CwYFNTHAMPo+R0RERERERPrWMaemJrILERERkT7FxcVht9txOByqqpGw8Hg8OBwO7HY7cXFxQbuvLWh3kojTP0YiIiIiIiKBmZU/jGc/KKO4rDbSSxEREZF+yM7O5uDBgxw4cID09HTi4uL8oyJEgsXj8dDW1obD4aChoYFRo0YF9f4KamKA/t0REREREREJjpneipqtBx20udzEWdWIQkREJJqlpaUBUFVVxcGDByO8Gol1drudUaNG+b/ugkVBTQwwvFNqVFAjIiIiIiISmMKsZNIT43A0t/HZ4XqmjU6P9JJERESkD2lpaaSlpdHW1obL5Yr0ciRGWa3WoLY760xBTQzwVdR4UFIjIiIiIiISCIvFYGZ+But2VVJcXqOgRkREZAiJi4sL2QvpIqGkGu4YoooaERERERGRwM3ytj/TnBoRERERCQcFNTHANxxLQY2IiIiIiEjgZhUMA6C4rCbCKxERERGRk4GCmhjg7Xym1mciIiIiIiJBMHN0BgD7jjVR09ga2cWIiIiISMxTUBMD/DNqlNOIiIiIiIgELD0pjqLhyQCUlNdGdjEiIiIiEvMU1MQAw1tTo5xGREREREQkOGblq/2ZiIiIiISHgpoYYHT0PhMREREREZEgmFWQAUCxKmpEREREJMQU1MQAzagREREREREJrpn5GQCUlNXidutnLREREREJHQU1MUAzakRERERERIJrUm4qCXEW6p3t7K1qiPRyRERERCSGKagREREREREROY7NamH66AwAPimrjehaRERERCS2KaiJCWZJjQpqREREREREgsc/p0ZBjYjIkORye9iw5xgvlhxkw55juNTKUkSilC3SC5DAdbQ+0382IiIiIiIiwTLLO6emuKwmsgsREZEBe23bYX708nYOO1r8+/LSE7hv6RQumpoXwZWJiHSnipoY4M1pVFEjIiIiIiISRLMKhgGw60g9jc72CK9GRET667Vth7n52U+6hDQAFY4Wbn72E17bdjhCKxMR6ZmCmhhgeEtqVFAjIiIiIiISPDlpCYxMT8DtgS0HHJFejoiI9IPL7eFHL2/v8Q3Nvn0/enm72qCJSFRRUBMDVFEjIiIiIiISGr6qmuJytT8TERkKPiyt7lZJ05kHOOxo4cPS6vAtSkSkDwpqYoDhT2oU1YiIiIiIiATTTP+cmtqIrkNERPrnaH3vIc1gzhMRCQcFNTHAF9QophEREREREQmuWQUZAJSU1+LRm+NERKLeiNSEoJ4nIhIOCmpigIFm1IiIiIiIiITC1FHp2CwGlfVODtY2R3o5IiLSh7mFmeSlJ/hHBRzPAPLSE5hbmBnOZYmInJCCmljgr6hRUiMiIiIiIhJMCXFWpoxMA9T+TERkKLBaDO5bOqXHY77w5r6lU7BaeotyRETCT0FNDNCIGhERERERkdCZpTk1IiJDykVT83jsmtPISo7vsj83PYHHrjmNi6bmRWhlIiI9U1ATAwxDrc9ERERERERCZaZ3Tk1xeU1kFyIiIv120dQ87l3SUVlzyohk/vX9cxXSiEhUUlATA1SoKSIiIiIiEjqz8ocB8OmhOpztrgivRkRE+quywel/3NLmVrszEYlaCmpiiApqREREREREgm9MVhLDkuJobXez43B9pJcjIiL9dNjR4n9cWe/Eo3Y0IhKlFNTEAG/nM/1nIyIiIiIiEgKGYTCrwKyqKS5T+zMRkaGioq4jqHG2u6l3tkdwNSIivVNQEwMMNT8TEREREREJqZn5GQAUl9VGdB0iItJ/FZ0qagCq6p29nCkiElkKamJAR0VNZNchIiIiIiISq2YVZABQUl4b0XWIiEj/HR/UVCqoEZEopaAmBvjqaTyaUiMiIiIiIhISM/IzMAwoq26iqkEv9ImIRDu328MRb+uz0cMSAajUv98iEqUU1MQCVdSIiIiIiIiEVFpCHKcMTwGgRO3PRESi3rHGVtrdHgwDpuSlAaqoEZHopaAmBvhm1CinERERERERCR3/nJrymsguRERE+uRrezY8xU5eegKgoEZEopeCmhjQMaNGUY2IiIiIiEiozCoYBkCxKmpERKJehbftWW56AsNT7QBqXSkiUUtBTQzomFEjIiIiIiIioTKrIAOALQccuNz6CUxEJJpVOJoByE3rCGpUUSMi0UpBTQww/CU1kV2HiIiIiIhILJuQk0pSvJUGZzu7jzZEejkiInICPVXUVKqiRkSilIKaGKCcRkREREREJPSsFoMZozMAKC7TnBoRkWh22NEpqEnRjBoRiW4KamKAv/WZZtSIiIiIiIiE1Exv+zPNqRERiW5HfBU1aQlkp8YDUNXQilutK0UkCimoiQG+ihoREREREREJrVn5GQCUlNdGdB0iInJinStqspLN1mcut4fa5rZILktEpEdDOqipqqqisLCQffv29Xj8oosu4qmnnvL/et26dUyePJns7GwefvjhLue+8MILjBkzhpEjR/Lcc8+FcNWho/cDiIiIiIiIhJavombX0XrqW/Rin4hINPJ4PFR4g5pRlmriy//FxMQ6QO3PRCQ6DdmgpqqqiiVLlvQa0qxatYrXX3/d/+vKykqWLVvGlVdeyYYNG1i1ahVr164FYNu2bVx99dX84Ac/4PXXX+fee+9l586d4fg0gsQsqVHnMxERERERkV44DkLpu+Y2ACNSExg9LBGPB7YccARpcSIiEkz1znaaWl182bqWgj+cAU8v5VXPzXzZulZBjYhEpSEb1Cxfvpyrrrqqx2PV1dXcfvvtTJw40b9v1apVjBw5kh/84AeMHz+ee++9lyeeeAKAlStXsnjxYm644QamTZvGt771LZ555plen9vpdFJXV9flI5J8rc88qqkRERERERHp7oPfwyOnwtNL4VdT4ZM/BHS7md72Z8VlNUFYnIiIBNsRRwu5HOOBuJUYHjcAVjzcb3uC+sp9kV2ciEgPhmxQs2LFCm677bYej91+++186UtfYt68ef59mzdvZvHixRjeVGPu3Lls2rTJf+zcc8/1n9v5WE8eeOAB0tPT/R/5+fnB+JQGzTeiRhU1IiIiIiIix3EchNfvxt8s2uOGl/8roMqaWQXDAM2pERGJVocdLRRaKrAe96Zmm+GmvXJPhFYlItK7IRvUFBYW9rh/7dq1vPXWWzz00ENd9tfV1XW5Ji0tjUOHDvV5rCd33303DofD/1FeXh7IpxIwX/ikoEZEREREROQ41XvMcKYzjwuq9w76lrO8c2qKy2rx6AcxEZGoU1HXQqk7F7f/7c2mdo+FfZ7cCK1KRKR3Qzao6UlLSws33ngjjz32GKmpqV2O2Ww27Ha7/9cJCQk0NTX1eawndrudtLS0Lh+RZPR9ioiIiIiIyMkpcxwYx/3oa1ghs2jQtzx1ZBrxVgvHGlspr24OcIEiIhJsFY4WKsjiw2FL/fs8GPx3+/XsdaZHcGUiIj2LqaDmxz/+MXPmzOHSSy/tdiwzM5PKykr/r+vr64mPj+/z2FDgn1Gjd3KJiIiIiIh0lT4Klv6aLm9xW/orc/8g2W1WJo8037BXXK45NSIi0aairgWAhE5vzD6YdwF/ci2mst4ZqWWJiPTKFukFBNPq1auprKwkIyMDgKamJv70pz/x4YcfMmfOHFavXu0/t7i4mFGjzG/M58yZw4YNG7j++uu7HRsKDO8PHIppREREREREenDatZCSA6u/DPGpMPPqgG85Kz+DzeW1FJfVctnMofPzo4jIyaDCYQY1YxtL/PuSPY0ACmpEJCrFVFCzfv162tvb/b++4447mDdvHl/72tcAuOWWW3jzzTdZtGgRDz30EBdeeCEAV1xxBWeddRbf/va3KSws5NFHH+Waa66JxKcwKB0VNZFdh4iIiIiISNQadx7EJUNrPRzdAblTA7rdrIIMnnofistrg7M+EREJmgpHC+k0kFH/uX9fktPsplPZoKBGRKJPTAU1o0eP7vLrlJQUsrOzyc7OBuCRRx7hkksuISUlhYyMDJ566ikAZsyYwbe//W1OP/10EhISGD9+PN/85jfDvfyAeVRTIyIiIiIi0jOrDfLnwN53oGxDwEHNaQXDANh+yEFLm4uEOGsQFikiIsFQUdfCHMtO8xdxSdDWRFzTEQBqmlppc7mJs8bURAgRGeKG/L9IHo+HsWPH9njsqaee8lfTANx0003s3LmTVatWsWXLFnJycvzHfvrTn1JcXMwLL7zA+++/T2JiYohXHjyqqBEREREREemHgjPNbdkHAd9q9LBEspLjaXN5+PRQXcD3ExGR4Ghpc1Hd2Mpcy2fmjokXA2BxOki2tOLxQHVjawRXKCLS3ZAPagaqsLCQiy++mJSUlG7HpkyZwgUXXEB8fHwEVjZ4mlEjIiIiIiLSDwXzzG35xoBvZRgGswoyACguqwn4fiIiEhxH68zWZvOs3qBmwkVmVQ0wIUlzakQkOp10QU0s8lXUiIiIiIiIyAmMOh0MKzjKobY84NvN8rY/K9GcGhGRqFFR10IyzUwxSs0dY+ZDai4A4xPrAQU1IhJ9FNTEELU+ExEREREROQF7CuRNNx8HoapmVn4GAMVltQHfS0REguOwo5nTLJ9jww0ZYyB9NKTmATA23mxVqaBGRKKNgpoY0FFRo6RGRERERETkhPxzajYEfKvp+RkYBhysbeZoXUvA9xMRkcAdqWvpmE8z5ixz6w1qRtscAFQ2KKgRkeiioCYG+GfUKKcRERERERE5sfwzzG3ZBwHfKsVuY8KIVACK1f5MRCQqHHZ0Dmrmm1tv67NcizlTTBU1IhJtFNTEAF9FjXIaERERERGRPhTMM7dHPoXm2oBvN6sgA9CcGhGRaHGsto6Zxm7zF/6gxqyoyXZXA6qoEZHoo6AmBvg6n3lUUiMiIiIiInJiqbkwrBDwwIGPAr6dL6gpLqsJ+F4iIhK41GObsRvttCQMh8wic2eaGdSkt1cBqqgRkeijoCYGqKJGRERERERkAII4p2ZWwTAAthxw0O5yB3w/EREJzJj6EgCa887oeNHMW1GT1FoJQJWCGhGJMgpqYoJm1IiIiIiIiPSbr/1ZEObUjBueQordRlOri11HGgK+n4iIDJ7L7WFy2zYALIULOg54Z9TYm48AHrU+E5Goo6AmBvgrapTUiIiIiIiI9M1XUXNwE7QH9mKd1WIwIz8dgOJytT8TEYmkY44GTjN2AZA8fmHHAW9FjaW9hTSaqG9pp6XNFYklioj0SEFNDPDPqInoKkRERERERIaI7PGQmAntLXB4c8C3m5Vvtj8rKasN+F4iIjJ4taWbSDacOEjBljOl40BcIiRkADDK5gA0p0ZEoouCmhhgaEiNiIiIiIhI/xlGkOfUZABQXF4b8L1ERGTwPPveA2BH/FSwHPeyp7eqZmJiPYDan4lIVFFQEwNUUSMiIiIiIjJA/jk1GwO+1cz8DAB2H23A0dwW8P1ERGRwkg6b/6aXp87qftA7p6YwwRvUqKJGRKKIgpoYoBk1IiIiIiIiA9S5oibAn6WyUuwUZCYBsFlVNSIikeF2M7z6EwBqsk/vfjxtJACj1fpMRKKQgpoYYPhrakRERERERKRf8maALQGaq6Hq84Bv52t/VqKgRkQkMo5uJ8FVT4MnAU/utO7HvRU1eZZaAKrU+kxEooiCmhiiehoREREREZF+ssXDKO87roMxp8bb/qy4rCbge4mIyCDsfx+ATe4J5GSkdD/unVEz3HMMUEWNiEQXBTUxoKP1WWTXISIiIiIiMqT459R8EPCtZhYMA6C4vFZtqUVEImH/vwDY6J5EbnpC9+PeipoMl4IaEYk+CmpiiEc1NSIiIiIiIv3nD2oCr6iZkpdGvM1CbVMb+441BXw/EREZAI8Hj7ei5kP3JHLTegpqzBk1Ka1VAFSq9ZmIRBEFNTFAFTUiIiIiIiKDMHoOYEBNKdRXBHSreJuFqSPTALU/ExEJu2O7MRorcXri2OIZd8KKmoSWSgzcqqgRkaiioCYGGN6kRjmNiIiIiIjIACRmQM6p5uMgtD+b5W1/VlJeG/C9RERkAPa/B0Cx5xSSkpJIiLN2PydlBGBgeNrJop6qBqdaVYpI1FBQEwMM3wP93yIiIiIiIjIwQZxTM6sgA4DistqA7yUiIgPgbXu2sbe2ZwDWOG9YAzlGDS1tbhqc7eFaoYjICSmoiQH+1mdKakRERERERAam4ExzG4Q5NTPzMwDYcbiO5lZXwPcTEZF+6jyfpqe2Zz7e9mdj4usA1P5MRKKGgpoYYHhralStKSIiIiIiMkC+ipqKLeCsD+hWozISGZ5qp93tYdshRxAWJyIifaotA0c5LsPKJ+7x5J0wqMkDYFyCghoRiS4KamJAR0WNiIiIiIiIDEj6aEjPB48bDnwc0K0Mw2CWt6qmRO3PRETCw1tNczBxIs0kkNNb6zPwV9Tk28wwvbJBQY2IRAcFNTHAN6NGA9BEREREREQGIahzaoYBUFxeE/C9RESkH/a/B8A221SAPipqRgIw0loLQJUqakQkSiioiQWqqBERERERERk8X1BTHnhQ45tTU6yKGhGR8PBW1HzgmgjQr4qaEVQDqqgRkeihoCYGaEaNiIiIiIhIAArONLflH4GrPaBbTR+djsWAw44WKhwtQViciIj0qv4IHNsNGKxtKgIgLz2x9/O9M2qGuY4BmlEjItFDQY2IiIiIiIic3IZPBns6tDXCka0B3SrZbmNibhoAJWp/JiISWmVmNY17xKmUN9sByD1RRU2aGdSktlUBCmpEJHooqIkBhtH3OSIiIiIiItILiwUKzjAfB2VOTQag9mciIiHnbXvWkDsXgMQ4K2mJtt7P91bUJLRWY6Ndrc9EJGooqIkBnXMaj/qfiYiIiIiIDJxvTk3ZhoBvpTk1IiJh4g1qKoadBkBuegLGid7RnJgJljgARlBLVX1ryJcoItIfCmpiQOf/gJTTiIiIiIiIDEK+L6j5IOAfrE7zVtRsOVhLm8sd4MIkKBwHofRdcysisaGpGo58CsDexOlAH23PwKygTM0FIMeooarBidutF9NEJPIU1MSALhU1EVuFiIiIiIjIEDbqNPNd1g1HoKY0oFsVZaeQmmCjpc3Nzor6IC1QBu2TP8CvpsLTS83tJ3+I9Iok3BTUxabyjYAHsiewz5kCmBU1ffK2Pxth1NDu9lDb3BbCRYqI9I+CmhjQuaJTrc9EREREREQGIS4RRs4yHwc4p8ZiMTran5XXBrYuCYzjILz8bfB4K5s8bnj5v/SC/clEQV3s2v+euR0znwpHC9DfoMasqCm01wFQWa85NSISeQpqYoDRqaZGMY2IiIiIiMggBXFOzayCYQAUl9UEfC8JQPWejpDGx+OC6r2RWY+El4K62OadT8OYszqCmr5an4G/omZMnANQUCMi0UFBTSzoUlETuWWIiIiIiIgMaQVnmtsAK2oAZnkrakrKagO+lwQgcxxdG4YDhhUyiyKyHAkzBXWxy9kAh0rMx2PmU1E3gIqaNDOoGWU1g5qqBgU1IhJ5CmpiQJfWZ6qpERERERERGZz8M8xt1S5orAroVr7WZ3urGqltag1wYTJo6aNg2JhOOwxY+itzv8Q+BXWx68CHZuiWUQDpowdVUZNjmBWPqqgRkWigoCYGdP6WQxU1IiIiIiIig5ScBdkTzcflGwO61bDkeAqzkwEo0ZyayGmugdqyjl9PuhROuzZy65HwSh8FudO67pv9VQV1saBT27N2l5tKb1VM3gBm1GS6jwH4rxURiSQFNTHAMIy+TxIREREREZG+BXNOjbeqpljtzyJn77qura/qD0duLRJ+rnao2Wc+zptpbjWfJjb4g5r5VDW04nJ7sFoMslLsfV/rrahJazcrJ1VRIyLRQEFNDFBFjYiIiIiISJD459QEVlEDMLMgA4BiVdREzp63zW3h2eZWs0lOLgc3gbMOEofB5Y+b+3a/CfUVkV2XBKatBQ58bD4ec5Z/Pk1Oqh2rpR9vZvYGNfb2BhJpUVAjIlFBQU0MUEGNiIiIiIgMRlVVFYWFhezbt8+/78UXX6SoqAibzcbMmTPZsWOH/9i2bduYM2cOw4YN484778QTi+8U81XUHCqGtuaAbjUrfxgAJWU1uN0x+HsV7Twe2LPWfHz69ea2uQaaqiO3Jgkvf1C3CIZPNOdQeVyw5Y+RXZcE5tAn4HJCSg5kFlHhMP+tzulP2zMAeyrEma0pRxi1VKn1mYhEAQU1McaDvvkXEREREZG+VVVVsWTJki4hzZ49e/j617/Ogw8+yMGDB5kwYQI33HADAE6nk6VLlzJ79mw+/vhjtm/fzlNPPRWZxYfSsLGQkgvuNjj4SUC3mpSXit1moa6lndJjjcFZn/Tfsd3gKANrPIy/wP8ueqpLI7suCZ+93qBu3LnmduZV5rZktVqSDGX73zO3Y+aDYVDhMCtq+jWfBsx3PHvn1ORSo4oaEYkKCmpigNGp+Zm+zxARERERkf5Yvnw5V111VZd9O3bs4MEHH+TLX/4yOTk53HzzzRQXFwOwZs0aHA4HDz/8MOPGjeP+++/niSee6PX+TqeTurq6Lh9DgmEEbU5NnNXC9NHpgObURISvmqJgHsQnQ2aR+Wu1Pzs5tDg62mONW2xuT/0S2BKh8rOAg1iJIP98mrMAOOxrfZbWz6AGIG2keY1RQ3VTK20udx8XiIiEloKaGNC59ZlyGhERERER6Y8VK1Zw2223ddm3ZMkSvvGNb/h/vXPnTsaPHw/A5s2bmTdvHklJSQBMnz6d7du393r/Bx54gPT0dP9Hfn5+CD6LEPHPqfkg4FvNzM8AoLisJuB7yQD5gppx55lbBTUnl9L1ZpuzzHGQUWDuS0iHyUvNxyWrIrc2GTxXe8cMsTHzATgy0Ioa6KiosdTg8UB1Y2tQlykiMlAKamJMTPaIFhERERGRoCssLDzh8dbWVn75y19y0003AVBXV9flGsMwsFqt1NT0HEDcfffdOBwO/0d5eXnwFh9qBWeY2/IPwe0K6FazCsw5NaqoCbP2VvOFeuhoe+UPavZEZk0SXse3PfPxtT/b9oI5lF6GlorN0NYICRkwfDIAhx2DqKjxBjVj4h0Aan8mIhGnoCYGqKJGRERERESC7b777iM5Odk/o8Zms2G327uck5CQQFNTU4/X2+120tLSunwMGTnTzEHTTgcc3RHQrWYVZADwWUUdTa3tQVic9Ev5RvPF3OThkDPV3KeKmpOLv6Jqcdf9hYsgbbTZGm3nK+FflwTG3/ZsPljMlzWP1PkqahL7fx/vzKrRVm9Q06CgRkQiS0FNDNCMGhERERERCaa3336b3/72t6xevZq4uDgAMjMzqays7HJefX098fHxkVhiaFltkD/HfBzgnJq89ERy0xJwe2DrAUcQFif94n+R/lz/i7lkjTO3x1RRE/Nq9puBnGGFsQu7HrNYYOaV5uOS1eFfmwSmc1CD2VnGV1GTO6CKGjOoybXUAqqoEZHIU1ATAzpX1KikRkREREREAlFaWsqVV17Jb3/7W6ZMmeLfP2fOHDZs2NDlPKfTSWZmZiSWGXqhmFNTXhvwvaSfOgc1PsO8rfuaq6FZM4Nimq/t2eg5kNBDNZ+v/dmet6HuUPjWJYFxu7sFNY7mNpztbgBGpNl7u7I7b1CT5akGFNSISOQpqIkBXXMaJTUiIiIiIjI4zc3NLFmyhMsuu4wvfelLNDQ00NDQgMfj4eyzz6auro4nn3wSgPvvv5/zzz8fq9Ua4VWHSME8cxuEoMbX/qy4TOFAWDRWweHN5uOiTm2v7CmQkmM+ri4N/7okfHpre+aTWQQF88Hjhs3Ph29dEpij26Gl1mxNmTsD6JhPk5kcT0LcAP4/8s6oSW+rAjwKakQk4hTUxADDUOszEREREREJ3BtvvMH27dtZsWIFqamp/o/9+/djs9lYuXIl3/rWt8jOzubFF1/kZz/7WaSXHDqjTjfbJtUdgNrygG41q2AYAMVltXj0Q1vo7X0H8JizhlJzuh7L9LY/05ya2OV2wd515uNx5+Jye9iw5xgvlhxkw55juNzev4Ozrja3Jav0YspQ4aumKTjDbFEJVHjn0+QMpO0Z+Ctq4jxO0mjUjBoRiThbpBcggVPnMxERERERGazOwcFll112wiBh2bJl7Nmzh02bNjFv3jyysrLCscTIsKdA3nQ4VGxW1WTkD/pW00alY7UYHK13ctjRwsiMAQy8loE7UTVFZhGUva+gJpYdKjGrLuzpvF6Txw+ffdtfdQGQl57AfUuncNGUy+DVO+HYbjjwEeTPjdiSpZ/2v2duvW3PACq8f7Z56QMMauISIHEYNNeQY9RSpYoaEYkwVdTEgM4zavTuLBERERERCaXc3FwuvfTS2A5pfPxzajac+Lw+JMZbmZyXCphVNRJCHk/P82l8Mr1zahTUxK695p9/RdZcblq9pUtIA+YL+zc/+wmvfd4AUy4zdxY/G+5VykB5PJ3m05zl3+0LagZcUQP+qppco1oVNSIScQpqYkCX1mcRXIeIiIiIiEhM8c2pKd8Y8K1m5mcAmlMTckd3QP1hsCV2BG2dZXlbnx3bE951SfjseQeAPxwt7PE1Et++H728HdeMq8xffPo3aG0Kx+pksI7tgcajYLXDyNP8uwddUQP+OTU5Ro1m1IhIxCmoEREREREREelJvjeoOfIpNNcGdKtZ+d45NeWB3Uf64KumGXuW2droeJlF5lYVNbHJ2eAPVl9pnNTraR7MIfQfuidDRgE46+CzV8K0SBkUX9uz0ad3+bvtm1GTO6iKmpEAjKCG+pZ2WtpcAS9TRGSwFNTEGHU+ExERERERCZLUHO8L+x5zhkUAZhVkALD1oIPWdnfga5OenajtGXQENU1V0OIIz5okfPa/B+42GpNGs9+T0+fpRxtaYebV5i9K1P4sqvnbns3vsttXUZMbQEXNSGstgKpqRCSiFNTECF/3M4+an4mIiIiIiARPkObUFGYnk54YR2u7m88q6oKwMOmmrbnjXfe9BTX2VEgeYT5WVU3s8QZ1DaMWAsaJzwVGpCbAjOXmL/aug9ryEC5OAtJbUFMXeFCTbzND2yrNqRGRCFJQEyP8334opxEREREREQke35yasg8Cuo1hGJ3m1NQGtibpWdkGaG8x2xkN773tldqfxbA9awHInnnRCWeWGJgzTeYWZsKwsTB2IeCBzc+HZZkyQLVl4CgDwwqj5/p3N7e6cDS3AYMNavIAyLOYs8NUUSMikaSgJkYY3pIa5TQiIiIiIiJB5JtTc3ATtAf2Ip6v/VlxWU2Ai5IedW57ZpygmiJrnLlVUBNbHAehaicYFqxFi7hv6ZQTnn7f0ilYLd6vE3/7s1XqKR+N9nsrGkfOBHuKf7evmiYp3kqq3Tbw+6aZQU22xxvUqKJGRCJIQU2M8H0Lqu8nREREREREgih7PCRmmpUahzcHdKtZBcMAKC6vDcLCpJvdvqBm8YnPyyw0t8cU1MSUvWY1DSNPg8RhpCbE9XhaemIcj11zGhdNzevYOWUZxKdATWnAbQ4lBHwtDY9re3bY0QyY1TTGicLZ3ngratJd1Vhwq6JGRCJKQU2M0IwaERERERGREDCMoM2pmTk6A4D9x5qobmwNcGHSRX0FHP0UMKCor6BGrc9ikrftGeMW43Z7eGDNDgCuPXMMz/3nPC6Zas4jmVeY2TWkAYhPhlO/aD4uWRWmBUu/+efTnNVl9xHffJq0QbQ9A3NelWHBioss6hTUiEhEKaiJEYa3pkYVNSIiIiIiIkEWpDk16UlxFA1PBqCkXO3Pgsr3Iv3ImZCcdeJzM32tz/aEdEkSRm53R0VN0WJe3nKIbQfrSLHb+PZ54zlzXBY3nWP+ub+/5xhtLnf3e/jan336d2htDM+6pW8NR+HY54DR8W+x12GHN6gZzHwaAKvNDGuAEUYNVWp9JiIRNKSDmqqqKgoLC9m3b59/34svvkhRURE2m42ZM2eyY8cO/7Ft27YxZ84chg0bxp133omnU6qxbt06Jk+eTHZ2Ng8//HA4P43g8FfUiIiIiIiISFD5K2o+MF8QDsCsfG/7s7LaABclXex5y9yOO7fbIZfbw4Y9x3ix5CAb9hzDlTHWPNBYCS114VujhM6RrdB0DOJTcOadxs9f3wnATYuKyEqxAzB1ZDqZyfHUO9v5ZH8PQWnBmTCsEFobYPtL4Vy9nIivmibnVEgc1uXQEUeAFTUAqWalVY5Ro4oaEYmoIRvUVFVVsWTJki4hzZ49e/j617/Ogw8+yMGDB5kwYQI33HADAE6nk6VLlzJ79mw+/vhjtm/fzlNPPQVAZWUly5Yt48orr2TDhg2sWrWKtWvXRuCzGryOGTWKakRERERERIIqbwbYEqC52vvO7sGbVZABKKgJKre7U9urrkHNa9sOs+Bnb3Plig/49vMlXLniAxb8ehNOe6Z5Qk1pmBcrIeH78x+7gGc/quBATTMjUu1ct6DQf4rFYnD2+GwA1u2q7H4Pw+ioqlH7s+jhb3s2v9shX0VN3mArasA/pybXqKFSFTUiEkFDNqhZvnw5V111VZd9O3bs4MEHH+TLX/4yOTk53HzzzRQXFwOwZs0aHA4HDz/8MOPGjeP+++/niSeeAGDVqlWMHDmSH/zgB4wfP557773Xf6wnTqeTurq6Lh+R5p9Ro5xGREREREQkuGzxMOp083GAc2p8Qc3m8lrcbv0AFxRHtkJTlTkMfvRc/+7Xth3m5mc/8b+Y61PhaGFrs/mCPcfU/iwm7HkbgOaCRfzP22aY+t0LJpAUb+ty2jkTzTZXPQY1ADOWAwbsWw81+0K1WhmIXubTQMeMmpwgVtToDdAiEilDNqhZsWIFt912W5d9S5Ys4Rvf+Ib/1zt37mT8+PEAbN68mXnz5pGUlATA9OnT2b59u//Y4sWLMbxpx9y5c9m0aVOvz/3AAw+Qnp7u/8jPzw/q5zYYhr+mRkRERERERILOP6dmY0C3mZiTSmKclXpnO3sqG4KwMPG9SM/YhWaohtnu7Ecvb++xPbgH2O/JAcB9bG941iih09rknx/1bGURtU1tnDIihX+bPbrbqQvHZ2MY8OmhOo7Wt3Q7TkY+FC0yH29+PpSrlv5oroEj28zHJ6yoSRz8c6SNBGAENbS0uWlwtg/+XiIiARiyQU1hYeEJj7e2tvLLX/6Sm266CYC6urou1xiGgdVqpaamptuxtLQ0Dh061Ou97777bhwOh/+jvLw8wM8mcKqoERERERERCSH/nJrAKmpsVgvTRqcDan8WNLu7z6f5sLS6WyVNZ/vcZlBTVbaj13NkiCh7H1xOXCkj+cUmc4bUXRdNwmbt/pJXVoqdaaPMv3/v7qrq+X7+9merA55JJQEq2wh4IGs8pIzocqjN5fa3KstJtw/+ObwVNaOs5tyiqobWwd9LRCQAQzao6ct9991HcnKyf0aNzWbDbu/6D3dCQgJNTU3djvn298Zut5OWltblI9JUTyMiIiIiIhJC+XMAw5xpUl8R0K38c2rKexhoLgPT2uivpuCU8/y7e6yW6GSfx3xx1lqripohzzufZpNtJs52D3PHZnLe5BG9nr5ownDgBO3PJi0BexrU7of97wV9uTIAvt//HqppzDZlYLMYZCcHEtSYM2pGWmv99xURiYSYDGrefvttfvvb37J69Wri4uIAyMzMpLKy63/C9fX1xMfHdzvm2z8UeXos7BYREREREZGAJKRDzlTzsS8YGKRZ+cMAVdQExb73wN0GGQWQWeTfPSL1xDMrfEFNalPkO2RIgPa+A8Azleaf/92XTPK3tu/JORPNoGb955W4epoTFZ8Ep37JfFyyOqhLlQE6wXyaik7zaSyWAN6+7A1qhmMG5wpqRCRSYi6oKS0t5corr+S3v/0tU6ZM8e+fM2cOGzZs6HKe0+kkMzOz27Hi4mJGjRoV1nUHyvdNiFqfiYiIiIiIhIh/Tk2AQY23ombXkXrNQwjUnk5tzzq9OD+3MJO89IReu0/4ZtTEN1eCU7OChqz6I3BkG24M/uWayiXTcplVMOyEl8wYnUFago3apjY2H6jt+aRZ15jb7X8HZ31Qlyz95GyAwyXm4x4qaiq8rQ1z008cyvbJG9Skux3E0U5lH9V4IiKhElNBTXNzM0uWLOGyyy7jS1/6Eg0NDTQ0NODxeDj77LOpq6vjySefBOD+++/n/PPPx2q1smzZMt577z3efPNN2traeOihh7jwwgsj/NkMjO+bT+U0IiIiIiIiIeIPagKbU5OTlsDI9ATcHtjS2wvF0j973ja3nebTAFgtBvctndLjz8gGUE8yrfHeF/Sr1f5syPJW03zqHkO9JZ07L5zU5yU2q4WF473tz3b20v5s9BzIOgXammD7i8FarQzEgY/A3Q7pBZCR3+2wP6hJCzCoScoEi9mNZwQ1/rk3IiLhFlNBzRtvvMH27dtZsWIFqamp/o/9+/djs9lYuXIl3/rWt8jOzubFF1/kZz/7GQDZ2dk88sgjXHLJJeTk5LBz507uueeeCH82A+RNajwqqREREREREQkNX1BTsSXgd9n73vWv9mcBqC2Hql1gWKBwUbfDF03N4zRv9VJnuekJPHbNacSPOMXcoaBmyPJ4K6r+5Z7GVWcUUJid3K/rFnnbn73T25waw4CZV5mPi1cFvE4ZBH/bs+7VNNDR+izgihrD8FfV5Bg1VNW3BnY/EZFBGvJBjcfjYezYsQBcdtlleDyebh++48uWLWPPnj08/fTT7Nixo0trtJtuuomdO3eyatUqtmzZQk5OTgQ+m8FTRY2IiIiIiEiIpY+G9HzwuOHAxwHdytf+TEFNAPaaQ+QZdTokZnQ73NzqYsdhM1D77gUTALAYsPaOc7hoah5kjjNPrN4TjtVKsHk8OHeZFVUfWWZy23nj+33poglmULPlQC3Vjb28MD/jSjMELHsfjulrJOz6CmqCVVEDkGYGNSOMWlXUiEjEDPmgZqByc3O59NJLycrK6nassLCQiy++mJSUlAisLDCaUSMiIiIiIhIGQZ5TU1Jeq84Ig7W703yaHqzdeZTmNhejhyXyrcWnkBhnxe2BQ7XN5gmZ5vB5VdQMTW2HPyWhpZJmTzyzF15Mdoq939fmpCUwKTcVjwfWf95LVU3aSChabD7e/HwQViz91u40W58BjDmrx1OCNqMGIDUXMCtqKusV1IhIZJx0QU2s6piZqG/wRUREREREQiZIc2pOHZmOzWJQ1eDkQE1zEBZ2knG7/PNJOOW8Hk95ZethAC6dlofFYjDW2xZrb2WjeYI/qCkN5UolRIrf+au5tZzK1xdNHPD1vvZn63prfwYw62pzu/k5cLsH/BwySAc/AZcTkkdA1rgeTwla6zPwtz7LNaoV1IhIxCioiRH+1mfKaUREREREREKn4Exze+BjcLUN+jYJcVamjEwDoLi8NggLO8kcKoGWWrCnw8jTuh1ubnXx9o6jAFwyzXwRtmi4GdSUVnmDmixvUKO2VkNOXUsbbbvMiqqEieeRFG8b8D3OmTACgHd3VeJ29/JiysRLza8xRznse3fQ65UB2v+euR0zv/M7k/08Hk9HUBOM1mepvtZnNVQ1OHv/ehARCSEFNTHC3/oswusQERERERGJacMnmy/ctjVCxdaAbjUrPwOA4rKaICzsJOMdIk/R2WDt/iL9ul0dbc+mj043T/VV1FQ1mCf5KmoaKqC1MeRLluBZuXY7p3m2AzD97C8O6h6zxwwjOd5KVUMr2w/X9XxSXAJMu8J8XLxqUM8jg+CfT9Nz27OapjZa280Kp5wgBjU51NDu9lDbPPgQXkRksBTUxAhV1IiIiIiIiISBxQIFZ5iPA55TMwyA4rLaABd1EtpjDpFnXG9tzyoAs5rG98ZGX0WNv/VZ4jDzA9T+bAipcLSw+f03SDRacSYMx5Y3dVD3ibdZmH9KNtBH+7OZ15jbHS9Di2NQzyUD4GqH8o3m4zHzezzlsMNsF5mdEk+8LQgvbXpn1Iy01gJQ1aD2ZyISfgpqYoSvEtSjmhoREREREZHQ8s2pKQ8sqJnprajZfqgOZ7srwEWdRFrqoPxD8/G4xd0Pt7l4a8cRoKPtGUBhdgoAe6s6Vc9keudfVKv92VDxyD93Mc+zGYD4Cef22Bqrv87xzql5Z+fR3k8adRpkT4T2Zvj0b4N+Lumnii3Q2gAJ6TBiSo+nHPG2PQtKNQ10qagBNKdGRCJCQU3M8LY+U04jIiIiIiISWr45NWUfBPRD2JisJIYlxdHqcrP9UC+tl6S70nfB4zJDlmFjux1+Z2clTa0uRmUkMsPb9gyg0Nv6rLLeSX2Lt7WRr/1Z9d5Qr1qCYNeRev68qZwFFrPtoNFLRVV/nT3eDGo+KavF0Vu7K8OAWVebj0tWB/R80g++tmcF880Kxh4cdphBTV56kIKaNDOoSaaJJFoU1IhIRCioiREBvIFEREREREREBmLkaWCNh4YjUDP4llmGYaj92WD4256d2+PhV7ceBuDiqbn+tmcA6YlxZKfEA1Dqq6pRUDOk/GzNZ2R46jjVst/cUXROQPfLz0xi3PBkXG4P7++u6v3E6f8BhtVsyVW1O6DnlD7sf8/c9tL2DOCII8gVNfZUiDcr7kYYNQpqRCQiFNTEGFXUiIiIiIiIhFhcAoycZT4OdE6Nt/1ZcXltYGs6mfiCmlO6V1N0aXs2Pa/b8SJv+zN/UJPlbX12TEFNtPtg7zHe+uwoC22fYsEDI06F1JyA77towgjArMTqVWounHK++bhkVcDPKb1wuzsqasac1etpQa+oAf+cmlyjhkrNqBGRCFBQEyN87xHSjBoREREREZEw8M2pKdsQ0G18FTUl5TWBrujkUL3XrGKy2GDsgm6H1+2qpLHVxcj0BH8I1pmv/dmeSlXUDCUej4cH1nwGwLUjvH9WPcwnGgzfnJp1uyrxnOjdrzOvMrebnwe3ZkqFROUOaKmFuGTIm97raRXBnlED/jk1I6ihShU1IhIBCmpihK+aWxU1IiIiIiIiYdB5Tk0ApuenYxhQXt2sdjv94aumyT/DbFd0HH/bs2l5Xdqe+RQNN4Oabq3P6g9Ba1Pw1ytB8erWCjaX15IUb2Fma7G5M0hBzdzCTBLiLFTUtbDrSEPvJ068GBKHmV8re9cG5bnlOL5qmvy5YI3r9bQKf0VNYvCe2xvU5KiiRkQiREFNjDDQkBoREREREZGwyT/D3FbtgsYTzLboQ1pCHKcMN9txlaj9Wd/2eF8g72E+jdn27CgAl0zr3vYMoMj7e7230vuCfFImJGSYjwOYNySh09ru5uevm9U035ttxdpwCKx2c9h8ECTEWZlXlAXAul1Hez/RZodp/24+LlkdlOeW4/jn0/Te9gw6Kmpy0+3Be+7Orc8UmotIBCioiRGqqBEREREREQmjpEzInmg+Lt8Y0K1mFWQAUFym9mcn5GqD0nfNxz0ENes/r6LB2U5eL23PoKP1WWlVY0ebK7U/i2rPfVjGvmNNZKfYuTJ7t7mzYB7EJwXtOc6ZYLY/O+GcGuhof7bjH9Csv69B5fF0mk/TewjX6GynvqUdgNxQVdQoqBGRCFBQEyM0o0ZERERERCTMgj6npjbABcW4Ax+Dsw4SMyFvRrfD/rZnU/OwWHruOlGQmYTVYtDU6uJInffF2Kxx5vbYnpAsWwavvqWNR9/6HIBvnz8e+/515oEgtT3zWTRxBAAf7aum0dne+4l5M2HEqeBywra/BnUNJ73qvdBwBKzxMGp2r6f5qmlS7DZS7LbgPX+ad0aNUUN1UyvtLnfw7i0i0g8KamKEr/euKmpERERERETCJEhzamZ6qz82l9ficuuHul755tOMWwwWa5dDznYXb24/AsAl03J7vUW8zUL+MPNd+HurvO3PVFETtR5/dy/HGlspyk5m+Wk5sO9f5oEeKqoCMTYriYLMJNpcHjbsOdb7iYbRUVWj9mfB5Wt7Nup0iEvo9TTffJrc9N7PGZROFTUeD1Q3tgb3/iIifVBQE2P0Lb2IiIiIiEiY+CpqDpUENIh+Qk4qSfFWGltdfH60Pjhri0X+oKaHtme7qqh3tpOblsBp3gql3nTMqWk0dyioiUpH6lpYud6cG/S9iyYSd2gTtDZAUjbkTAvqcxmGwTkTve3PTjSnBmD6f4DFBgc/hsqdQV3HSa0fbc+gU1CTFuygpmNGDXg4qvZnIhJmCmpiRMeMGkU1IiIiIiIiYTFsLKTkgrsNDn0y6NtYLQYzRmcAUFxWG5SlxZym6o7f46Luba98bc8umprba9szn85zagDI9LY+U1ATVX715i6a21ycVpDBhafmwt615oGic8AS/JezFnWaU3PC11ZShsP4L5iPS1YFfR0nLV9FTV9BTV1oK2rstJFOI5UNCmpEJLwU1MQIf1AT2WWIiIiIiIicPAwjiHNqMgAoLtOA8h6VrgOPG4ZPgvRRXQ45213809v27NLpeX3eqmi4GdTsrTyu9VndQWhrDt6aZdB2H63njx+VA/Dfl0w2273v8QY1QZ5P4zOvKIt4q4UDNc0dIV5vfO3PNj8PrhPMtJH+qS2H2jIwrJA/94SnhqyixmY3519htj+rVEWNiISZgpoYYaAZNSIiIiIiImHnn1OzMaDb+ObUlJTXBraeWOVve3Zet0Pv7TbbnuWk2ZndR9sz6KGiJikT7Onm45p9wVitBOhnr+3E7YELpuRw+thMaK45YUVVMCTbbcwpNL9+1u2qPPHJ4y+EpCxoONLxtSmD5wu682aAPfWEpx4O1Ywa8FfV5BrVCmpEJOwU1MQI48SV3SIiIiIiIhIKvoqa8g/B7Rr0bWZ6K2o+P9pAXUtbEBYWQzyeTtUU3efTvLKlAoCLp+b12fYMYJx3Rk15TTOt7W7zB+osb1XNsT3BWbMM2kf7qvnn9iNYLQbfv2iSubP0XbOiKntit4qqYDpnwgjAbH92QrZ4mPZl83HJsyFbz0mjn23PwJxdBCGoqAH/nJoco4YqtT4TkTBTUBNzVFIjIiIiIiISNjlTIT4FnA44umPQtxmRmsDoYYl4PLCl3BHEBcaAqs/BUQ5We7cXclvb3fxzuxnUXDKt77ZnACNS7STHW3G5PZRV++bUeIMazamJKI/Hw/2vmn+Pvnx6PqeMMEO1joqq0FTT+CyaaM6p+WDvMVra+gheZ11tbneuMWcoyeDtf9/cjjmrz1NDWlGTZv4bMoJaVdSISNgpqIkRvvcMqfWZiIiIiIhIGFltMHqO+TjgOTVm2yXNqTmO70X6MWdCfFKXQ+/trqKupZ3hqXZmj+m77RmAYRgU+ufUKKiJJq9tq6C4rJbEOCvfOX98x4ETVFQF0/gRKeSlJ+Bsd7OxtI/wJXea+eFqhW1/Cem6YlpDJVTtMh/7KhR70dru5lijGaCEsvWZZtSISCQoqIkRhrf3mXIaERERERGRMPPPqfkgoNv45tSs/ewoL5YcZMOeY7jc+imvo5qih7ZnWw8DcPHUXKz9aHvmU5htVmrs9c2pyRxnbqvV+ixS2lxuHnp9JwD/ubCQEb7WVtV7oXY/WOL6VXERCMMwOMdbVfPOzqN9XzDTW1VTrPZng1bmraYZcao5L+oEjta34PFAvNVCZlJ88NfibX2Wa1RTqdZnIhJmCmpihCpqREREREREIsT3LvAAgxqnt9XSJ+W1fPv5Eq5c8QELfvY2r207HOgKh652J+xbbz4+LqhpbXfzxqcDa3vmU5RtVtSUdquoKR38WiUgz39YRmlVI1nJ8Xxj0biOA76gLn8u2FNCvo5FE8ygZt2uPubUgDmnxhIHh0vgyKehXVis8rU9G9t3COebTzMizd6veVQDljrSvL8qakQkAhTUxArv/08eJTUiIiIiIiLhNfp0MKxQdwBqywd1i9e2Hebn3mqCziocLdz87Ccnb1hTvhHamiB5hDkPqJP39phtz7JT7MwZe+J34h+vyNf6rKrB3JHlDQYcB6CtJeBly8A0ONv59VufA/Dt88eTYrd1HPS3PQvtfBqf+adkY7UY7K1spLy66cQnJ2fBhAvNxyWrQ7+4WLT/PXN73Pypnvjm0+SFou0Z+Ctqcoxa6lva+55TJCISRApqYoS/oiaiqxARERERETkJxSdD3nTz8SCqalxuDz96eXuPP8/59v3o5e0nZxu0zm3PjK7voH91y+DangEUeVuflfpanyVlgT0N8EDNvkBWLIOw4t29VDW0UpidzJVzCzoOuNqh9F3zcVFo59P4pCXEMds7L+qd/lTVzLrG3G75I7jaQriyGNRcCxXbzMcFfQc1Fd6gJictVEGNWZk3nFosuKlS+zMRCSMFNTHCP6PmJPy+XUREREREJOL8c2o2DPjSD0ur/e8U74kH853kH/Y13DwW9TKfps3l5o3tR4CBtz0DGJudBEBVQyuO5jYzBMosNA9W7x38emXAjta3sGK9+Xt+54UTibN2eqnq0CfgrIOEDBg5M2xrWuSdU7NuZz+CmlPOh+Th0FgJn/8zxCuLMeUbAQ9knQKpOX2eXhHqiprk4WBYsBlusnCo/ZmIhJWCmhjRUVGjpEZERERERCTsAphTc7S+f622+ntezGiohMObzcfHtb16f88xHM1tZKfYmVs4sLZnAKkJcYxItQOdqmoyve3PqvcMeskycL9+83OaWl3MzM/g4qm5XQ/62p4VLQKLNWxr8s2peX9PFa3t7hOfbI2D6f9hPi5ZFeKVxZgBtD0DqKgLcUWN1QYpZmCUozk1IhJmCmpihKHeZyIiIiIiIpGT7w1qjm6H5poBXToitX8vOvb3vJix9x1zmzsNUkZ0OeRre3bR1JwBtz3zKcz2zqmp9M6pySwyt6qoCZs9lQ08/5E51+nuiyf5u4V0nOCtqCoKz3wanyl5aWSn2GlqdfHx/n5Uss28ytzueg0aq0K7uFiy/31zO+asfp3eUVGTGKoVdZpTU0OlWp+JSBgpqIkRhremRjmNiIiIiIhIBKTmeF/o90D5RwO6dG5hJnnpCfQWNxiYrX4GUzkypJ2g7dnr2ysAuGTqwNue+RQNP25OjYKasHvotc9wuT2cP3kEZxRldT3YUgcHvH+XxoU3qLFYDH9VTb/an+WcCnkzwd0OW/8c2sXFitZGOFRsPh5gRU1uuj1Uq/LPqck1aqiqbw3d84iIHEdBTYzwvelEM2pEREREREQiZJBzaqwWg/uWTgHoNay5b+mUQVeODEkeT69BzYY9x6htaiMrOT6g8KrIX1HjDWqyvK3PjimoCYeP91Xz+qdHsBjw/YsmdT9h33rwuMwAbdjYsK/PP6dmVz+CGoBZ15hbtT/rnwMfmcFWej5kFPR5utvt4Yg/qAl9Rc0Io4bKhpOs3aSIRJSCmhijGTUiIiIiIiIR4ptTU75xwJdeNDWPx645jdzjhmTH2yw8ds1pXBRA5ciQdHQ7NFSALbEjAPN6davZ9uzCqbnYrIN/WaNouDeoOb6ixlEO7Wp5FEoej4cH1nwGwJdPz2d8Tmr3k3zzaY4L6sJl4SnZGAZ8VlHvb7l1QlOvAGs8VGyFw1tCv8Chzt/2rH/VNNVNrbS5PBgG/vlSIZE6EoAcNKNGRMJLQU2M6NbHVURERERERMLLFygc3DSoF/ovmprHv75/Ls/95zzuWzIFA2htdzMmKzm46xwKfNU0YxeAreNF2TaXm9c/NdueXTotsPDKN6OmtKoBt9sDycMhPgXwQM3+gO4tJ/bG9iNs2l9DQpyF71wwoeeT9nqDmjDPp/EZlhzPjNEZAKzbdbTvC5IyYeIl5uOS1aFbWKwYYFDjC8uyU+zEBRDQ9slbUZNrKKgRkfBSUBNj1PpMREREREQkQrJOgaQsaG+Bw5sHdQurxeDMcVl8fUEhl0w3g4iV60uDucqhoZe2Zxv3VlPT1EZmcjxnBDizJz8zCZvFoKXNbc6+MIxOc2r2BHRv6V27y83PXjOraW5YUEROWkL3k2rL4NhuMKxQuDDMK+xwzkDbn8282txu/RO0a75Jr9qdHfOHxpzVr0t8QU1uT18vweSdUZNj1FDZoKBGRMJHQU2M8NXTKKcRERERERGJEMMY9JyanvznQjM0eGnzQf9shpNCW3PHu+2PC2pe8bU9OzWwtmcAcVYLBZlJQKc5Nf6gRnNqQuWPH5ezt7KRzOR4blxU1PNJvrZno0+HhPTwLe44iyaYQc36z6tod7n7vmDcuZCSC03H4PPXQ7y6IexQsRloJw83A+5+OOyfTxPioCbNDGpGGDVU1bfi0TuiRSRMFNTECF/nM/0HIiIiIiIiEkG+OTVlHwR8q5n5GZw+ZhhtLg9Pv78v4PsNGfvfN1/ETRsFwyf6d7cHse2Zj29OTWlVg7lDQU1INTrbeeSfnwNw27mnkJoQ1/OJvoqqCLU985k+OoNhSXHUt7RTXF7b9wVWG8z4D/Ox2p/1bv975nbM/I4XtPpwJMwVNVlGPa62FhpbXaF9PhERLwU1McIf1ER2GSIiIiIiIie3/E5Bjbsf78Dvww3eqppVG8toam0P+H5Dgr/t2eIuL+JuLK2murGVYUlxzCsKrO2ZT9HwFPMpfRU1WePM7TG1PguFletLqWpwMiYriavOGNPzSW4XlK4zHx9XURVuVovBwvHe9mc7B9j+bNfr0NCP2TYnI/98mv61PQM47AhTRU3iMLDGAzDCqNWcGhEJGwU1McJASY2IiIiIiEjE5c0AWwI0V8OxzwO+3QVTchiTlYSjuY0XNh0IwgKHgF7m0wSz7ZlPYbavokatz0Ktst7J/75rBmB3XjiReFsvf4aHN0NzDdjTYNTsMK6wZ772Z/2eUzN8Iow6HTwu2PKnEK5siHK1Q9lG8/GY+f2+zNf+MeQVNYYBqbkAjKBGQY2IhI2CmhjRUVGjpEZERERERCRibPHmi7QQlDk1VovB9QsKAXjiX6W43DH+M1/dYTi6HTC6tL1qd7l5fZvZ9uySILU9AyjyBjV7/a3PvBU1jnINgw+yR9/6nKZWFzNGp5+4dZ0vqBu70GwlFmFne4OarQcdVPV3uPzMq8xtySpQi/quKrZAa705e2jElH5fdtjRDEBeqCtqAFJHApBjKKgRkfBRUBMjfMXg+v9fREREREQkwoI4pwbg32aPJj0xjv3Hmvjn9iNBuWfU2usdIj9yFiR1tDf7sLSaY42tZCTFcea4rKA9XaF3Rs2Bmmac7S5IGQFxyeBxQ+3+oD3PyW5vZQPPfVgGwF0XT8Y40VySve+Y23GRnU/jMzzVztRRaQC829+qmqlXgNVuho6HS0K3uKHI1/as4EywWPt92ZE6MzDJCUtQY1bU5Bg1/Q/nREQCpKAmVni/yVFQIyIiIiIiEmEFZ5rbIFTUACTF27hmXgEAK9fHeEuu3W+Z297ank3JJS5Ibc8AhqfYSbXb8Hhg/7Em82drtT8Lup+/vpN2t4dzJ404cdDmbOgIOCM8n6azAbc/S8yAyUvMx8WrQrOooco/n6b/bc/qW9pocJozukLe+gwg1az4ylVFjYiEkYKaGOGvqInoKkRERERERIT8OYABNfvMVl5BcO2ZY4mzGny8v4bispqg3DPquN0dFTWnnOff7XJ7eP1Tb9uz6cFrewZgGIa/qmZvpXdOTZY3qDm2J6jPdbL6pKyGNdsqsBjw/Ysmnfjk/e+Duw0yCjoCsyiwaMIIwKyo6Xf7QV/7s61/hna92A+Yf8fLfEHNWf2+zDefJjXBRrI9DO3w0sx/Z0YoqBGRMFJQEyP8M2pUUiMiIiIiIhJZCemQM9V8XB6c9mc5aQksmzEKgJXrS4Nyz6hTsQWajkF8Coye49/9YWk1VQ1m27P5QWx75tN9To0qaoLF4/HwwKs7ALOF38Tc1BNf4AvqihZ3vNARBWYVZJBqt1HT1MbWg47+XVS02Jx10lILO9eEdH1DRuVn0FwDcUmQN6Pflx12mEFNWObTgL+iJocaKtX6TETCREFNjFBFjYiIiIiISBTxz6nZGLRb3rCwEIA12w5TXt0UtPtGDd8Q+cKzwRrn3/2qt+3ZF6bkBLXtmU9hdgoApb6KGgU1QfPmjqN8tK8Gu83Cdy6Y0PcFvq+BKJlP4xNntbBgfDYA63b2s/2ZxQozlpuPS9T+DID975nb/Lld/o73pcIb1OSEo+0Z+GfU5BrVqqgRkbBRUBMjDM2oERERERERiR7+oCY4c2oAJuelsXB8Nm4PPPnevqDdN2r4X6TvmE3icntYs81se3bxtOC2PfMp8rU+q/IFNePMbbVanwWi3eXmwTVmNc31CwrJS0888QV1h8yKCwwoXBT6BQ5Qx5yao/2/aObV5nb3m1BfEYJVDTH7B972DDqCmnBX1IwwaqlSRY2IhImCmhgRPQXBIiIiIiIiQsGZ5rZiCzjrg3bbGxaa1R5//KgMR3Nb0O4bcb0Mkf9oXzVVDU7SEmycNS47JE9d6G19Vlp1XEVNbRm0t4bkOU8Gf950gD2VjQxLiuOmc8b1fcEeb9uzkbMgKTO0ixuERRPNoKakvJbapn5+XWSfAvlngMcNm58P4eqGAI+nU1Azf0CXVnhn1OSGuaIm1WimuaEWd3/nEomIBEBBTczRfx4iIiIiIiIRlz4K0gvMF2gPfBy02549PpsJOSk0trp4/sOyoN034va/5x0iP6bLEHl/27NTc4m3heYlDF9QU93Yar4An5prztDwuMFRHpLnjHVNre088s9dANx67njSEvrR5so3n6ZTUBdN8tITmZiTitsD6z+v6v+FM68ytyWrT+42KNV7oaECrPEwavaALj3iC2r6qsoKFnsqnnizJeIwd01sheIiErUU1MQI34y9k/n/fBERERERkajib3/2QdBuaRgGNywwg4yn3t9Hm8sdtHtH1O63zO24c/0/4HZue3ZpiNqeASTbbf536u+tajSf3xcWHVP7s8F4Yn0pR+ud5GcmcvW8gr4vcLth7zvm4yibT9OZr6pm3a5+zqkBOPVLYEuEqp1w8JMQrWwI8FXTjJoNcQMLXA47fEGNPdir6pXhbX+Wa1RTqfZnIhIGCmpihOFtfqacRkREREREJEqEYE4NwGWzRpKdYuewo8VfcTLk+ebTnHKef9em/TVU1nvbnp0SmrZnPv45NZW+9meF5rZ6b0ifNxZVNTj533fN37c7vjARu83a90VHtkFjJcQlw+i5IV7h4HXMqanE0993yiakw+Sl5uOSZ0O0siFgkG3PoKOiJidcrc8A0rxzajD/HRIRCTUFNbFCFTUiIiIiIiLRxRfUHPgYXMFrnWO3WfnqmWMAWLF+b/9fMI5WtWVw7HMwrDB2oX+3L4S6YEro2p75+Nqf7a1sMHf4KmqqVVEzUP/z1uc0ONuZNiqdpdNH9u8iX9uzsQvAFh+6xQXo9LHDSIq3UlnvZPvhuv5fOOtqc7v1L9DWEprFRbv975nbAQY1znYXVQ3mTKC8cLU+A/BW1OQYNVSpokZEwkBBTYzw5jR4VFMjIiIiIiISHYZPBns6tDVCxdag3vqaeWNIiLOw7WAdH+ytDuq9w843RH706ZCYAYDb7WHNNjOouXR6bsiXUDTcnEdRWuWrqBlnblVRMyD7qhpZtdGcnXT3xZOwWIw+rvDyVVRFcdszMEPS+eOygAG2Pxt7NqTng9MBn/0jRKuLYo4DULsfDAvknzGgS4/WmSFJvM3CsKR+zDoKllTz351cQxU1IhIeCmpihGbUiIiIiIiIRBmLBQq8L0oGcU4NwLDkeP5t9mgAVq4f4mHCHt98mk5tz8pqOFLnJDUMbc8AirKPb33mq6gZ4r+3Yfbz13fS7vZwzsThzO/vn1tbM+z3tgccd27oFhck/vZnOwcQ1FgsMONK83HJ6hCsKsr5/nzzZoA9dUCXVnjbnuWmJWAY/Qz+gsFbUTNCQY2IhImCmhihGTUiIiIiIiJRKERzagCuO6sQw4C3PjvK7qMNQb9/WLhdnYbId7xI/8oWb9uzyTn9m3ESIN+MmtJjjbjdHsjyVtTU7A9q27pYVlJeyytbD2MY8P2LJvX/wrIN4HJC6kjInhC6BQbJogkjAHOGUn3LAL42ZnqDmj1vg+NgCFYWxfxtz84a8KUVjo6gJqw6tT5TUCMi4aCgJkZ0VNQoqhEREREREYkaBWea27IPgt4CoWh4CudNygHgiX+VBvXeYXOoGFoc5sD1kbOArm3PLpmWF5ZljMpIJM5q0Nru5mBtM6Tkgi0RPC5zho6ckMfj4YFXdwBwxWmjmZyX1v+LO7c9C2fFxCAVZCVRlJ1Mu9vDe7uP9f/CzCIomA94YMvzIVtfVNr/vrkd4Hwa6BTUpEcoqKGGSs2oEZEwUFATI4bA9zIiIiIiIiInn5GngTUeGo+GpI3Wfy4sBOCvnxzg2FB8MXG3t+1Z4SKw2gD4xNf2zG5j4YTQtz0DsFktjMnyVtVUNZqtqjLN31uqh2gIFkZvf3aUjaXV2G0WvnvBAKti9rxjbodA2zOfs33tzwYypwZg1tXmtmT1ydO7vqESqnaaj33B9QD4W5+FPagxZ9TkGLVUetcgIhJKCmpihL/12Uny/7yIiIiIiMiQEJfgrxQJ9pwagLmFmUwfnY6z3c2zHwzByg9fNcUpHfNpXtlqVtOcPyU8bc98Cv1zarxt5PxzavaEbQ1DUbvLzYNrPgPga2eNZWRGYv8vbjgKR7aajwsXhWB1obFoom9OzdGBdTaZchnEJcGx3VD+YYhWF2V8bR9HnApJmQO+PHKtz8ygxm600dYwgMopEZFBUlATI/ytzzSlRkREREREJLr45tSUBz+oMQyDGxaagcIzH+yjpc0V9OcImRYHHPjIfFy0GDDbnr22rQIIX9szH/+cmqpGc4c/qAl+JdRQ53J72LDnGC+WHOSh1z/j86MNZCTF8c1zThnYjXzziXKnQ8rwoK8zVOYVZhFvs3DI0TKw+VD2VJjyRfNxyaqQrC3qBND2DCJYUWOz407MAiCu+QjtLnd4n19ETjoKamKMKmpERERERESiTOc5NSFwydRcRmUkUtXQyt+Lh9CQ8tJ3zRkwWafAsDEAFJfXctjRQordxsLx4Wl75lPkq6hRUHNCr207zIKfvc2VKz7g28+X8Pi7Zmu48yeNID0xbmA327PW3I5bHORVhlZivJV5ReaL+ANufzbzKnO77a/Q2hTklUWh/e+Z28EGNZGaUQMYad72Z9RQ3dga9ucXkZOLgpoYYWhIjYiIiIiISHTKP8PcVu2Cxqqg395mtfC1+WMBWPmvUtzuIfIOPv8Q+Y62Z6/62p5NHkFCXPjangEUDU8BYG+lN6jJGmduj6n1mc9r2w5z87OfcNjRfWbHXz45yGvbDvf/Zh5Px9dA0dAKagAWDXZOzZizIGMMtNbDZ/8IwcqiSIsDKryt7QYR1LjdHo7URaj1GWCkmlV9I4wajtYPwRlgIjKkKKiJMaqoERERERERiTJJmTB8kvm4fGNInuI/5uaTYrex+2jDwF84jhR/UGMOkXe7PazxBjUXh7ntGXTMqDnkaDZbyPkqamr3g6s97OuJNi63hx+9vP2EDdd/9PJ2XP0NCis/g4YKsCUMash8pPmCmo17q2lqHcDXh8XSUVVT/GwIVhZFyjYCHsgc55/5MhBVjU7a3R4sBgxPtQd/fX3xBjU51FDZoKBGREJrSAc1VVVVFBYWsm/fPv++bdu2MWfOHIYNG8add97ZZajbunXrmDx5MtnZ2Tz88MNd7vXCCy8wZswYRo4cyXPPPReuTyFofPU0ymlERERERESikG9OjW+wdpClJcSxfE4+ACv/NQRadVXvhZp9YImDsQsAKDlQyyFHC8nxVv+L4OGUlRxPWoINjwf2HWuE1JFmiOBuB0d52NcTbT4sre6xksbHAxx2tPBhaXX/bugL6sbMh7jwV0sEatzwZEYPS6TV5eaDvQMcNj9jubktfRdqy4K/uGgRYNuzIw4zHMlOsRNnjcBLmL6gxqihShU1IhJiQzaoqaqqYsmSJV1CGqfTydKlS5k9ezYff/wx27dv56mnngKgsrKSZcuWceWVV7JhwwZWrVrF2rVmL9Rt27Zx9dVX84Mf/IDXX3+de++9l507d0bgsxo8X+czj0pqREREREREok+I59QAfH1BIVaLwXu7j/HpIUfInicodr9lbgvmgd1sOfbqFrOa5rzJOWFvewZmS/HCzu3PLBYYVmgerFb7s6P1vYc0gzmvYz7NuYNcUWQZhtHR/mznAKvYho2FsQsBD2z+Y9DXFjX2v29ux5w1qMsPO5oByIvAfBrAXwWUa6iiRkRCb8gGNcuXL+eqq67qsm/NmjU4HA4efvhhxo0bx/33388TTzwBwKpVqxg5ciQ/+MEPGD9+PPfee6//2MqVK1m8eDE33HAD06ZN41vf+hbPPPNMr8/tdDqpq6vr8hFpqqgRERERERGJYr45NYdKQjZAfFRGIpd4W4Y9sb40JM8RNMcNkfd4PKzZVgHg/xwiYZy3/VlplXdOja/9WXWU/36GwYjU/r1Y3q/z2p0d1RZDcD6Njy+oeWcw7QZnXm1uS1bFZh/71iY49In5eLAVNd75NDkRmE8DQNpIwJxRU6mKGhEJsSEb1KxYsYLbbruty77Nmzczb948kpKSAJg+fTrbt2/3H1u8eDGGt/Rk7ty5bNq0yX/s3HM73sHR+VhPHnjgAdLT0/0f+fn5Qf3cBsPwl9REdh0iIiIiIiLSg2FjISUX3G0dL16GwA0LzAqQlzYfouIEbaoiytVmtnwCfzXF5gMODtY2kxxv5ZyJ4W975lM03Axq9lQ2mDsyvRU1x1RRM7cwk7z0BP8bRY9nYFY+zC3M7Ptm5RuhrQmSR0DOqcFcZljNPyWbOKvB/mNN7POFe/01ZRnEp0BNachaIkbUgY/MtoFpoyGjYFC38LXai3RFTY6CGhEJgyEb1BQWFnbbV1dX12W/YRhYrVZqamq6HUtLS+PQoUM9Xtf5WE/uvvtuHA6H/6O8PPK9ajsqapTUiIiIiIiIRB3DCPmcGoAZ+RnMHZtJu9vDU+/vC9nzBOTAR9BaD0lZkDsDgFe3mm3Pzo1Q2zOfwmyz9Zm/oiZrnLmtHgJzf0LMajG4b+mUHo/5XpO4b+kUrJbeopxOOldUGf04P0ql2G2cPsYMptYNtKomPhlO/aL5uHhVcBcWDfxtz+YP+s+4wldRE7GgxqzuG04tx+pCUwkpIuIzZIOanthsNux2e5d9CQkJNDU1dTvm29/TdZ2P9cRut5OWltblI9I6ZtREdh0iIiIiIiLSizDMqQG4YaH5RsTVG/fT6GwP6XMNim+IfNFisFjweDy84p1Pc+m03AgurKOiZm9lozkD1t/6TEENwEVT83jsmtNIju8apuWmJ/DYNadx0dR+tq3r/DUwxC3yVoC9s/PowC/2tT/79G/gbAjiqqKAr7XdINueAf6qwIhV1CQPx2NYsRoeXPVHIrMGETlpxFRQk5mZSWVl13cw1NfXEx8f3+2Yb39P13U+NnSYSY1yGhERERERkSjlq6gp/xDcrpA9zfmTcyjMTqaupZ0/fxz5DhDd+F6k97Y92+Jte5YUb+WciSMiuDAYm2UGNY7mNmqa2iDTW1FTsw9cURh6RcBFU/OYVZABwH/Myee5/5zHv75/bv9DmqZqOLzZfDwuBoIa75yaDXuP0dI2wL/XBWfCsEJoa4QdL4VgdRHS3mpWzgGMOWvQt6mI9IwaixVXkvnna2lUUCMioRVTQc2cOXPYsKGjhLy0tBSn00lmZma3Y8XFxYwaNarH6zofGypUUSMiIiIiIhLlcqaaMymcdXB0e8iexmIxuM47q+b/3tuHyx1FPyg2VcNB74we74v0vrZniyeNiGjbM4DEeCujMhIB2FvZAGmjwGo3ZwvVHYjo2qKFx+Nh26E6AK45YwxnjsvqX7szn73vAB4YMcU/A2Qom5SbSk6anZY2Nx/tqx7YxYbRUVVTsjr4i4uUQ8XQ3gJJ2ZA9flC38Hg8nSpqEoO5uoHxtj9Laa0aeBAnIjIAMRXUnH322dTV1fHkk08CcP/993P++edjtVpZtmwZ7733Hm+++SZtbW089NBDXHjhhQBcccUVPP/882zdupWGhgYeffRR/7GhQjNqREREREREopzVBqPnmI9D3P7s304bTUZSHGXVTbzxaUVIn2tAOr9InzbSbHu21df2rJ8VGSFWmO1tf1bVCBYLDBtrHlD7MwAO1jZT29RGnNVgQm7KwG8QQ23PwJyP7KuqWbdzgHNqAGYsBwzYt96s3IoFndueDXI+Tb2znaZWMxjJjVRFDWBNN/9dyjWqqWpwRmwdIhL7YiqosdlsrFy5km9961tkZ2fz4osv8rOf/QyA7OxsHnnkES655BJycnLYuXMn99xzDwAzZszg29/+NqeffjqjRo3CarXyzW9+M5KfyoCpokZERERERGQICNOcmsR4K9ecMQaAFeujKGA4ru3Z1oMODtQ0kxhnZXGE2575dJ5TA0CWt/3ZsT0RWlF02XbQAcCEnFTstgFWQHk83rAO/9dALFg0wfzafWfXIIKajHwoWmQ+LnkuiKuKIH9QE0DbM281TXpiHInxkau0M9JGAjDCqKGyXkGNiITOkA9qPB4PY8eO9f962bJl7Nmzh6effpodO3YwZcoU/7GbbrqJnTt3smrVKrZs2UJOTo7/2E9/+lOKi4t54YUXeP/990lMjGBZ5SAYmlEjIiIiIiIS/XxzakIc1ABcO38M8VYLn5TVsml/Tcifr08eD+xZaz72tj3zVdOcO2lERF+M7cxXUVNa5R3unllkbqtLI7Si6LLtoNn2bOrI9IFffGw3OMrBGh/QkPlos2B8NlaLwe6jDRyoaRr4DWZeY243rwa3O7iLCzdXO5RtNB8H8GfsC2oiWU0D+Nvz5VBLVUNrZNciIjFtyAc1PcnNzeXSSy8lKyur27HCwkIuvvhiUlK6l+dOmTKFCy64gPj4+HAsU0RERERERE42o08Hw2rOO6ktD+lTjUhN4LKZ5rvBn/hXFFTVVO0yP2+rHQrm4/F4WLPVbMt2SZS0PQMoGm6+XuCvqMk05/2o9Zlpq7eiZuroQQQ1vqCuYB7EJwVxVZGVnhjHrPwMAN7dVTXwG0y6FOxpUFsG+/8V3MWF25Gt0FoP9nTIOXXQt/EHNemRDmo6Wp+pokZEQikmg5qTkb/lp3qfiYiIiIiIRK/4ZMibYT4OQ1XNDQvNapDXtlVQXj2Id/oHk6/t2Zj5EJ/Ep4fqKKtuIiHOwuJJwyO7tk6KvBU1+4814XJ7INPb+qxarc88Ho+/9dnUkWkDv8Feb1ATI/NpOvPNqXln59GBXxyfBKd+yXxcsjqIq4qA/e+b24J5YBl8lVxFXXRV1Kj1mYiEmoKaGOGfURPZZYiIiIiIiEhf/HNqNoT8qSbmpnL2hOG4PfDEvyLcuuu4+TSd254lxdsitapuRmYkEm+z0Opyc7CmuaP1Wc0+cLsiurZIO1Ln5FhjK1aLweS8AQY1rjYoXW8+HheDQc1EM6h5f88xWtsH0b5slrf92ad/g12vgeNgEFcXRr6gJsDWdoejpqLGrErMMWqobGiJ7FpEJKYpqIkR/hk1SmpERERERESiWxjn1ADcsMBs3fWnj8txNLWF5Tm7aXfCPm9Lp3Hn4vF4eNUb1ERT2zMAq8VgbJbZlmtvVQOkjzZnqrhawXEgwquLLF/bs/EjUkiIG2C1xIGPzZZYiZmQOyMEq4usqSPTyUqOp8HZzidlg5gJNXoOJI+A9hZY/R/wq6nwyR+Cv9BQcrs7BTVnBXSrI3XREtSYFTWZRgM1dfWRXYuIxDQFNbHCV1GjpEZERERERCS6+YKao9uheRAv6A7QwvHZTMpNpanVxeoPy0L+fD0q+wDamiAlB3JO5dNDdew/1oTdZmHxxBGRWdMJFGV3mlNjscKwseaBk3xOjb/t2ajBzKfxVlQVnQOW2Hs5ymIxONvb/mzdrsqB36DuEDR2us7jhpf/a2hV1lTthOZqiEvqaPE4SFFTUZM4DJfFnGXtrquI7FpEJKbF3v+MJyn/iJqIrkJERERERET6lDLC207LA+UfhfzpDMPgem9VzVPvlw6uLVOgOrc9Mwx/Nc3iiSNItkdP2zOfwuHmnJq9VQ3mDl/7MwU1QIDzabyt72JRx5yaQQQ11Xvo9qqOxwVbXxg67VP2v2duR88BW3xAtzoSLTNqDIO2ZLOqxqhXUCMioaOgJkYYhlqfiYiIiIiIDBlhnFMDsGzmSIan2jlS5+SVrYfC8pxddApqurQ9mx5dbc98irLNoKa0qtHcoaAGgG2HzKBm2ugBVtQ018LBTebjGJxP47NwfDaGATsO1/mDhn7LHAdGDy/TvXkv/N9FsGdt9L/oE6S2Zy1tLqobWwHIi3RFDUCKGdTENx1RJxsRCRkFNTFCFTUiIiIiIiJDSJjn1NhtVr42fywAK94tDe+LjQ1HoWKL+bhoMTsO17PP2/bsvEnR1/YMoMhXUVOpoMbnaH0LR+qcWAyYnDfAiprSd81WXlnjzZk/MSorxc50b1u4dwfa/ix9FCz9NRje2T+GxWwTZ0uA8g/gmS/Ck5fA3nXRGdh4PJ2CmvkB3eponRMAu81CemJcoCsLmC1jJACZ7mM0troivBoRiVVBrS9uaWlhx44d7Ny5k6qqKhoaGrBYLKSmppKXl8fEiROZOHEilhjsRRpphmbUiIiIiMj/z959x7dVmPsf/0iyLe/txCvDdhYhYWQRMliBBhISSqGMtpdbWtpCS6Ethf7ovbSXe3uhpfcWaCm0BUpoC2VzmSmUTQYEssggcWI703tJnrIt6ffHkRQ700PWkeTv+/XyS/aRfPQ4iZ3kfPU8j4hEDn9HzcH10OOCGPuwP+VXzxjLA+/sZnuVk7VlDcybkD3szwlA+XvGbe4pkJzD66t3AnDO5JywHHsGh3bUVDk6ae/qIVFBDdsOOgEoyUkmMW6Av28jYOyZ39mTcth8wMF7pXV8edaYgX3yjGugZJHx5yyz2AhvWqph1b3w6WOwbw38ZbnRsXLO7VC0cHi+iMFoqoCWKrDGQuGsIZ2qytEBGN00/gkyZopJM4KaUZYm6lpcJIfpzy0RiWxDTkwcDge/+93vWLRoEenp6cyaNYuvfvWr3Hzzzfzbv/0bt99+OzfeeCOXXXYZ06ZNIzMzky996Us8/fTT9PT0BONrEA511IiIiIiIiPRXfX09RUVF7NmzJ3Bs69atzJ49m4yMDG699dY+LwZ7//33Oemkk8jOzuY3v/mNCRVHkawJkJgFbhdUbgrJU6YnxnH5TKOb4eEPQxg4HGvs2fTwHHsGkJEUR3qi8Ur+ivo2yCox7misAI8JO37CwBb/fpqCAY49g15/BqJ37Jnf2ZONPTWrdtXT4x7En5W0AiOASSswPk7JhYt+BTdvgjnfBlucsQvm8YthxcWwZ3Xwih8KfzdNwUyITRjSqap9Y+NGm72fxi/F+Fk12tJEfavL5GJEJFoNOqhpbm7mxz/+MQUFBfzgBz/g3Xffxe12c/LJJ3P55Zdz4403cvvtt3Pbbbdxww03sHTpUoqLi3E6nfzf//0fX/nKVygsLOS3v/2tApsg0I4aEREREREZiPr6ei6++OI+IY3L5WLZsmXMnDmTTz/9lO3bt7NixQoA6urqWL58OVdffTVr167liSee4N133zWn+GhgsYR8Tw3ANxcUYbHAuzvr2F3bMvxP6PX2CWp2VLdQXt9GXIyVRSeNHv7nH4I+e2pSC41OAbcLnAdNrswcW31Bzcn5Axx71lgBTXvAGgPjFwS/sDBzamE6aQmxODq62XzAEbwTp+bDkl/DTZtg9nVGYLPnQ1ixBB5fBntD93PkqII09gyg2mEENWGxnwYOBTUYHTUiIsNhUEHNX//6VyZMmMC9995LR0cHixYt4qmnnqKuro7PPvuMp59+mvvvv59f/OIX3H333TzwwAO8/PLL7Nq1i3379vH73/+e6dOnU1tbyw9/+EOmTZvGRx+FZi5vtDq0o0ZJjYiIiIhIpGlsbOSss86ivr4+ZM951VVX8ZWvfKXPsZUrV+JwOPjNb35DSUkJd911F48++igATzzxBPn5+dxxxx1MnDiRn/3sZ4H7jsblcuF0Ovu8yWH8e2r2fxyypxyfncQFvoDk0VUVw/+ENdugtQZiE2Hs3EA3zdmTcsJ+fFCRb/xZeV0b2GIgY5xxxwgdf+YPaqYPtKPGP/ascA7YU4JcVfiJsVlZMNEYK/j+ztrgP0FaASz9X7hpI8z6hhEgVnwAj10If7kE9oXu50kfe32dPePmD/lUgY6asAlqcgGjo0ZBjYgMlwEFNW1tbVx++eV8/etfp7GxkfPOO48NGzbw5ptvcsUVV5Cenn7CcxQWFnLDDTewadMmXn31VSZPnkxpaSkLFy7kv/7rvwb7dYhmn4mIiIiIRKy77rqLVatWMXv2bD744IOQPOfDDz/MTTfd1OfY5s2bmTt3LomJiQCccsopbN++PXDfueeeG+jmnzNnDuvXrz/m+e+++27S0tICb2PGDHBXw0gQ6Kj5KKTjtL51lrFv5fkNB4d/jI+/m2b8Ary2OF7zBTVLw3jsmV9xTq+OGoBM//izMpMqMk9Dq4tKX5fD1IF21IygsWd+Z08yxp+9X1o3fE+SVggX3ws3bYCZXzc6lsrfgz9/Af56Kez/ZPie+3COg0bXlMUKY+YM+XSBjpowHH2moEZEhku/g5qKigrOOOMMXnzxRZKTk3nkkUf45z//yamnnjroJ1+yZAmbN2/mlltuwePx8B//8R9cccUVuFz6oTdYGn0mIiIiIhJZ9u/fz+9//3sA9u3bx+7du0PyvEVFRUccczqdfY5bLBZsNhtNTU1H3JeamkplZeUxz3/77bfjcDgCb/v37w/uFxANck+BmAToaISGXSF72lnjMjh1TDpdPR7+unbv8D5Zr7FnO2taKK/zjz0bNbzPGwT+0Wflda3GgUwj4BqJHTVbK42OuOLsJFLiY/v/ie4eo9sDoOS8YagsPJ3jC2o+O+igYbjD0PSxsOx++P4GmHGNEdiUvQOPng9/uwwOHDtQDxr/+MbcUyB+gEHeUfg7anLDrKMm2dKJo7nJ5GJEJFr1K6jZsmULCxYsYPv27ZSUlLBu3Tq+8Y1vBKWA2NhYfv3rX/PCCy+QkJDA888/z8UXX0xHR0dQzj9SWHwtNcppREREREQiy0033YTL5cJisbB48eKg/V9rMGJiYrDb7X2OxcfH097efsR9/uPHYrfbSU1N7fMmh4mJg8JZxvsh3FNjsVj41kIjdPvrR3vp7HYPzxN1tR/aW1GyiNc/M7ppzpqYM7CL/SYpzvGNPqtvw+v19gpqQjAyLswE9tMMdOxZ5UbodEB8GuSfPgyVhadRqfGclJeK1wurdodopGXGOFj+O/j+ejj9X8Big91vwSPnwRNfhoPDGNgEcewZHOqoyU1LCMr5hsyeTFeM8fPA7Tz2CxRERIaiX0HNn/70J6qqqpgzZw4ff/wxkydPDnohl1xyCe+88w4pKSl88MEHrF1r8hK0COObPqCOGhERERGRCHLffffx0ksvYbFYyMjI4OGHHza1nszMTOrq+o7qaWlpIS4u7oj7/MdliPx7avaFdm/rhSfnUpCeQGNbFy9sODg8T7JvDbhdkFoI2RN5fWs1AEtPyR2e5wuycVmJWCzQ0tlDfWsXZPmCmoaRN/psW6V/P80AA1f/fpqis8FqC3JV4c0//uy9ncM4/uxoMsbDJQ8Ygc1pXzMCm11vwsPnwZNXGuFZsPkD2fFDD2rcHi+1vvFiueEy+gzoTjC6AK0tVSZXIiLRql+b++6//35GjRrFzTffPKyvgpozZw5vvPEG+/fv57zzRk5LbDD4V9R41VMjIiIiIhIRPv74Y37yk59gsViw2+28+OKLxMfHs3btWhISEkhISCAmJoaYmJjAXpjjcbvd9PT00NbWRmtrKwsWLBhwTbNnz+4TFlVUVOByucjMzGT27Nk8+eSTgfs2btxIQUHBgJ9DDhMIakL7YsUYm5Vr54/nF699ziOryrlq9his1iAvPy3zXaQvOZfS2lZ217YSZ7Oy6KTRwX2eYRIfa6MgPYEDTR1U1LeR4++oaaowdgpZB7T2N6Jt8XXUTMsfYEdNrz8DI805k3P4w/tlfFBah8fjDf7314lkFsEXfw8LfwQf/A989hSU/sN4m3QRnPP/IP+0oT9PWz3U7TDe9+/dGoL6Vhdujxeb1UJOiv3EnxAinpQ8aCknpr3G7FJEJEr1K6ixWq3ccccdw10LAGeccQZnnHFGSJ4rmqijRkREREQkcnz++edceumldHd3Y7VaWbFiBQsXLuT555/niiuuGPL5LRYLPT09A/68s846C6fTyWOPPca1117LXXfdxfnnn4/NZmP58uV873vf46233uLss8/mnnvuYfHixUOudcQrnA1YjEXczipIzQvZU185ewz3v7WL8ro23iut5bwpQQ5Qdr9t3E5YxGv+sWeTskmNgLFnfkXZSRxo6qC8rpU5Y8ca+z96OqGl0ljmPgI42rvZ32iMpx/Q6DNXCxxYZ7xfPPKCmhljM0i2x9DQ1sW2SifTCwcYcgVLVglc+hCc9WN4/x7Y8gyUrjTeJi81Apu8UwZ/fn/IPGoqJGYOuVz/2LOcZDu2UIdbx2FLy4NKSHTVmhO8iUjUGzkv/4hyFvQXhIiIiIhIJNi4cSNnn3021dXVWK1Wfv/73/cJZ7xeb1DeBiMmJoZHHnmEG2+8kezsbF566SV+9atfAZCdnc29997LkiVLGD16NDt37uTf//3fg/JrMqLFp8Hoacb7+0M7/iwlPparzxgLwMMfBHnvirMS6j4HLFB0Nq9vMYKaJdNDF0QFQ4lvT01FfRvYYiB9nHFHY7mJVYXWVt/Ys7GZiaQlDCBk27MKPD2QUWR0d4wwcTFW5pVkAfDezlqTq8EIbL70R/jeOph+BVissPM1+ONCeOqrUL11cOf1jz0bNy8oZVYF9tOEz9gzgLgMo4M0x9uIo6Pb5GpEJBr1q6NGwt+hjhq11IiIiIiIhKt33nmHyy+/nObmZuLj43niiSe49NJLA/eXlJTwgx/8gKSkJOLj44mLi8Paj/FKXq+Xzs7OwJvL5ep3TYf/H2L58uWUlZWxfv165s6dS1ZWVuC+66+/nsWLF7Njxw4WLlxIcnJyv59HjmPsXKjZYuypOfnSEz8+iL4+bzyPrqpgbXkDWw86mDbQZfHH4h95VTCDXS2x7KptJdZmiZixZ37FOUkAlNW1GQcyi6GxzAhqis4ysbLQ2XrQv59moGPP3jFuR+DYM7+zJ+fw5vYa3i+t4/uLJppdjiF7Ilz2MJx1K7z/K9j6POx41Xg7abnRYTP65P6fb+9q4zZIQU2N0xfUhNF+GoCY1HwARlmaqG91kZGkHW0iElwKaqKERp+JiIiIiISf7u5uYmNj6ezs5Cc/+Qm///3v8Xg85OTk8MILLzB/ft/Fy6eddhqnnXaaOcX2kpuby9KlS496X1FREUVFI+/V8cNq7Fz45OGQ76kByE9PYOn0PF7eXMkjH5Zz31WnB+fEZb6xZyXn8Zqvm2bhxJyBdWSEgaJsI6ipqG81DmSVwO5/QkOZiVWFln8/zckFA9xZHNhPM3J3EJ89KQeADfuacLR3k5YYRn/+cybB5Y8eCmy2vQifv2y8Tf2iEdiMOun45+h0QPUW4/2x0d1R4x9LOdrSTF2Li4mjU0wuSESijUafRQ0jqVFOIyIiIiISPm688UZuuOEGTjvtNB544AE8Hg8XXnghW7ZsOSKkkRHMv4C7eoux1yPEvrWwGIBXP6uiytEx9BN6PL0u0i+K2LFnAMW+0Wf7GtvpcXuMjhoYUaPPtlU6gQF21DTvh4Zdxnit8QuHqbLwV5iRyIRRyXi8sGp3vdnlHN2oKfDlx+C7a42ABmD7/8GDZ8Kz10LtjmN/7v514PV9XwRpv1agoybcgpoUX1BDE3Wt/e9aFRHpLwU1UUIdNSIiIiIi4aW+vp6//e1v/OlPf6K0tBSLxcK9997L66+/zqhRo8wuT8JJWgGkjTUueB74JORPP70wjTOKMunxeFmxZs/QT1i9GToaIS6F3XGTKa0xxp5dMDWyxp4B5KXGEx9rpdvt5UBTR6+gJsg7fcKUs7Pb2M8DTMsfQFBT7h99NxMS0oNfWATxd9W8XxoGe2qOZ9RJcMXjcMMaYwQaXtj2Ajw4F577JtSVHvk5QR57BgTC4rywC2pyAWP0WZ0vTBIRCSYFNVHCl9PgVU+NiIiIiEhY+O1vf0tHRwderxeLxYLX6+Xvf/87mzdvNrs0CUdj5xq3+z4y5en9XTVPfryPVlfP0E7m301SdBavb28AYMGE7IgbewZgtVoYn2WMPyuvb+3bUePxmFhZaGz3ddMUpCcMbCeHxp4FnDPZH9TURcZe4dEnw5V/hetXwUnLAC9sfQ4ePAOe/xbU7z702L1rjNtxwesQrXEa3Sqjw2xHDclGUGO39NDaFOahm4hEJAU1UUIdNSIiIiIi4eXf//3fee2117jkkksCQc0nn3zC7Nmz+dGPfkRHRxBGTEn0MDmoOW/KKIpzkmjp7OGZT/YP7WS7fUHNhPMieuyZX3GOL6ipa4P0sWCxQU8HtFabXNnw2+rbTzNtIPtpPB4of894v/jc4BcVYWaPzyQ+1kqN08XOmtCPNhy03Olw5d/gOx/ClIuNjr8tz8DvZ8ML3zFGNR5Ybzw2syQoT+n1esO3oyYmjo7YDAC6HZUmFyMi0UhBTZSwBHpqREREREQkHMTFxXHRRRfx4osvsm3bNq666ioAenp6uP/++znjjDPYtWtXn8/p7Ozk3/7t3/jjH//Iq6++yoYNG6isrKSnZ4gdDhL+/HtqDnwK7u6QP73VauGbC4oA+PPqCmMfy2C4WmD/xwDszZjLjuoWYqwWvjA1N1ilhlxxtrGnpry+DWyxRlgDI2JPTSCoGcjYs16j7yicNUyVRY74WBtnFmcB8N7OOpOrGYS8U+CqJ+A7H8DkJUZg89lT8IcF4PX93fTYhbDhL0N+KmdHD53dxs+esOuoAVwJvrGlTgU1IhJ8CmqijBpqRERERETCz+TJk3nyySf5+OOPmTt3Ll6vl23btjF79mxeeOGFwOMaGhq4++67+e53v8sll1zC7NmzGTNmDHa7nczMTCZNmsSCBQv4l3/5F37729+ye/fu4zyrRJScKRCfBt1txivVTfCl0wvJSIzlQFMHb2yrGdxJ9qwGTzdkjOflvXYA5k/IJi0x8sae+RVlGx01FXXGrhayfN0DDWUmVRQ6W/xBTeEAghr/2LOihUawJYf21ERiUOOXdypc/Xf49ntQdE7f+7weeOUH4Dg4pKeochrdNBmJscTH2oZ0ruHgTjIC55i2Qf58FBE5jqAGNR6Ph/3797Np0yY+/PBD1qxZw8aNG6mqqgrm08hRWAJLahTViIiIiIiEq1mzZrF69Wp++ctfEhcXh9Pp5IorruD3v/89APv27QOM8S+HvzU3N7N7927WrFnDk08+yQ9/+EMmT57Meeedx3vvvWfiVyVBYbXCGHPHnyXE2fiXueMAePjD8sHt0yh727gtWcRrvrFnSyN47Bn0Gn1W32oc6L2nJoq1uXqMLiIG2FHj31GksWcB50w2OjE+3ds49B1QZss/Hc665cjjXveQvyeqHZ1AeHbTAFjT8gGId2lHjYgEX8xQPtnhcPDMM8/w7rvv8vHHH7Nv3z48x1imFxcXx9SpU5kzZw6LFy9m6dKlxMbqlRXBEshpTK1CREREREROxGKxcNtttzF//nyWL19OU1MTN910Ex0dHXzzm9/kww8/xGaz4Xa76erqoq2tjdbWVhwOB01NTezdu5ePPvqIzZs3A/D++++zaNEivvKVr/Dggw+SkpJi8lcogzZ2Lux6A/athTO/a0oJ/3LmeP7wQTmb9jezYV8TM8dlDuwEvov01Tnz2LHKN/bs5NHDUGno+Eef1ThdtLl6SAoENdHdUbO9yonXC7mp8eSk2Pv3SV1tgdF3lJw3fMVFmPHZSYzLSmRvQztrdtfzhZMjdxQgYOyksViNTho/i+1QiDlI/qAm7PbT+MSlG0FNSnc9PW4PMTYNKhKR4BlUUONwOPjZz37Gww8/jMvl6terbFwuFxs3bmTTpk386U9/Ii0tjR//+MfcdtttxMQMKS8SjP/sgRpqREREREQixfz58/nwww+54IILqKqq4ic/+QkWi4VbbjnKK5WPorS0lF//+tesWLECt9vNk08+ySeffMLrr79OcfHQLpaJSfx7avZ9ZPznzhL6XaQ5KXYuPa2Apz/dz8MfVDDzXwYQ1DTthYbdYLHxirMEqGTehGzSE+OGrd5QSEuMJSspjoa2Lirq25jmX5zeWGFuYcMssJ+mILX/n7R3Dbi7IG3MoRFxAhjjz/6ydi/vl9ZFflCTVgDL7jfGnXndRkiz7D7j+BBUO42gJjdMg5qErEIARtNEY3sXo1LCs04RiUwDjn537tzJ6aefzgMPPEBnZydz5szhf/7nf1i7di21tbV0dho/VC0WC6tXr6alpYX9+/ezatUqfve733HppZcSFxdHc3Mzd9xxB3PnzqW5uTnYX9eI5VVPjYiIiIhIxJg6dSqvv/46KSkpeL1efvKTn/DKK6/063MnTZrEww8/zAcffMC4cePwer2UlpaycOFCSktLh7lyGRb5p4MtDtpq4bOnh7zvYbCuW1gEwBvbq9nb0Nb/Tyz37SYpnM2L240xYUunR/gFaR//npry+ra+o8+i+NWSWw86AZhWMIj9NCXnmhI0hrNzJvv21JTWDW6sYLiZcQ38YAv866vG7YxrhnxKf0dNbmrCkM81HKypRkfNaEsTdS0uk6sRkWgzoKDG6XRy0UUXsWfPHsaNG8c///lP1q5dy49+9CPOOOMMsrOziYs79EoZm81GUlISBQUFzJs3j+9973s899xzHDhwgG9/+9t4vV42btzIxRdfjNvtDvoXN5L4//0TDX/Xi4iIiIiMJKeeeirPPfccNpsNj8fDV7/6VbZs6f8y+TPPPJO1a9cybdo0AKqqqrjkkkui40LgSBMbD6m+V6S/+B24bxps+EvIy5g4OoVzJufg9cKfVw2ga2S3sZ+mKX8h26uc2KwWvjA1OoKawJ6aulZIH2uMfepuh5ZqkysbPoGOmoHsp/GHddpPc4S5xVnE2awcaOqgrG4AAWg4SyuAooVD7qTxO9RR089Re6GWYvw8U1AjIsNhQEHN3XffzZ49e5g6dSrr1q1j0aJFg3rSrKws/vCHP3Dvvffi9XpZu3YtK1asGNS5xGDxbanRf8VERERERMLH7373O5qamk74uAsuuICf/vSnAOTk5Ax4PHRubi5vvvkm48ePJz09nb/+9a+B8cgSQRwHoWnPoY+9HnjlZnAcCHkp1y0wukae+fQAze1dJ/4Edw9UvA/A210nAzCvJIuMpMgee+ZX5NtTU1HfBjFxRlgDQ16eHq46utzsqm0BYHphP4MaZxXUbgcsUHzOsNUWqRLjYphTZIwSfL+0zuRqwlOgoyYtPDtqSMkDIBsH9Y4oCdtEJGwMKKh57LHHSExM5OWXXyY7O3vIT37zzTezaNEivF4vv/71r4d8vpFMHTUiIiIiIuGlsrKSm2++mXHjxnHLLbewb9++4z7+5z//Oddccw0ffvghJ5100oCfLzc3l+eff54VK1Ywa9aswZYtZmos44iX33k98Mez4bUfQ9k70NOP0CQI5k/IYkpuCh3dbp74+Ph/dgGo3AidDohP5/E9GQAsnZ43zFWGzqGOGt/F2d7jz6LQ59VOPF7ITrYzKqWf3Q3l7xm3+adB4gB2G40gZ086NP5MjhToqEkN090vSdm4sWGzeGlrqjK7GhGJMv0Oavbt20dtbS2XXHJJUBdTfuUrXwFgz549QTvnSOR/rZx21IiIiIiIhIe//MUYWdXW1sZ9993HhAkTuOKKK/jggw+O+nir1cqKFSvIz88f9HOefvrpLF++fNCfLybLLDFGah2uvR4+eRj+ein8egI8903Y+jx0OoetFIvFwrcWGv/3f3zNHrp6PMf/hDJj7Flb4UK2VLUZY88ifWF6L8XZh0afeb1e4/cKfOFa9NnmG3s2vSC1/915Ze8Ytxp7dkz+PTUflzfQ2a0VAL11drtpbu8GIDctTIMaq422uCwAupsqTS5GRE7E7fGytqyBlzYdZG1ZA25PeF8373c/fWursQiwqyu4r97xn8/jOcE/+uS4LIeSGhERERERCQPJycmceeaZfPzxx3g8Hnp6enj++ed5/vnnmTp1KkVFRUF7Lq/XS09PD93d3XR2dtLe3s6GDRuCdn4JkbQCWHY/vPID8LrBYoMlvzb21ux4FUr/AW11sPU5480aC0VnwZSlMHkJpAa3g2XZqfnc88YOapwuXtlcyWUzC4/9YN9F+nXWUwE4sziLzCgZewYwNisRqwXautzUtbgYFeUdNVv8+2kK+jn2zOM51FFTct7wFBUFJoxKJj8tnkpHJ2vLGzh38iizSwob/rFnCbE2UuMHNv4zlDrjR5HaVYvHqY4akXD2j61V3PnKdqp8P1sA8tLi+fmyqVw4LTw7fvv9k2/8+PEkJyfz6quvcuDAAQoLj/MPtH7yeDz87ne/w2KxDHrfjRj8r3BRTiMiIiIiEh5uvPFGbrzxRurq6njxxRd57LHH+PjjjwHYvn0727dv7/N47yDnGB/+anev16v9NJFsxjVQssgIADKLDy3pnnwheNxw4FMjtNn5OjTsNjpZyt6G134E+TOM0GbKUsiZ0usVfYMTF2PlX+eN555/7OThD8v50oyCo//Z6mg26gL+UmsEGEuiaOwZgD3GRmFGIvsa2ymra4v6oGbrQaNbq99BTe02aKuF2EQYM2cYK4tsFouFsyfn8Pd1+3l/Z52Cml78F1Pz0uLD+u8wd9JocG7F1qagRiRc/WNrFTf8bcMR18mrHZ3c8LcNPPS1GWEZ1vQ7qElMTOT73/8+d999N9deey0rV64c8ILLw/2///f/2L59OxaLhe9///tDOtdIF2io0ZIaEREREZGwkpOTw7e//W2+/e1vs2XLFv73f/+Xp556iq6uLiwWSyBYOemkkwY19qy7u5uOjg5cLhcul4vu7m5NLIh0aQWHAprerDYYe4bx9oX/grrSQ6HNgU+gcoPx9s5/QUbRodBmzBnG5w7CV+aM5Xdv72ZHdQurdzewYOJR9tVWfABeN93pJbxbHY/NamHxyaMH9XzhrDgniX2N7VTUt3FmiW/0WUO5sSw2jC8sD1Rnt5vSmhZgAEFN2bvG7bj5ENPPnTYj1NmTRvH3dfv5QHtq+qjx7acZHa77afxS86EK7B21ZlciIkfh9ni585XtR21m8GJcQ7/zle1cMDUXmzW8/u4eUNJy66238vjjj/POO+9w4YUX8vjjj1NQcJR/PJ5AS0sLt9xyC48++igWi4UrrriCJUuWDPg80kt4/bkSEREREZGjmD59OitWrOCuu+7iF7/4BY8++ijd3cZM/r1793L55Zdz++23Ex8f5heqJDzkTIKcH8HCH0FLNexcaYQ25e9BUwWsfcB4S8yGSRfClCXG/pC4xH4/RXpiHFfMKuTxtXt5+MPyowc1vrFnO5KNToq5xZlkJUffxfqi7CTe21lHeV0rzPTtE+pug9ZaSImeYKq0poUej5eMxFjy+7srpNwX1Gjs2QnNm5BFjNVCeX0b+xraGZvV/+/HaNa7oyacxaUbL6hI6lLQJhKO1lU09hl3djgvxs+bdRWNnFmSFbrC+uEoWwqPLT09nbfeeousrCzeeecdJkyYwLXXXssLL7zAnj17jujmsFgsuN1uamtr+eCDD7j//vu58sorycvL49FHH8Xr9XLRRRcFlmzK0KmhRkREREQk/OXn5/Pggw/y+eefc/HFF+P1euno6OAXv/gFJ598Mm+++abZJUqkScmFWdfCV5+F28rhy4/DKVdCfBq018Omv8FTX4F7iuHvX4GNT0BbQ79O/Y0FRVgs8H5pXaDTIsDrNUavAS86JwHRN/bMrzgnGYCK+jajayTNNxI+ysaf9d5P068RVN2dsHeN8X7JucNYWXRIjY9lxrgMAN4vVVeGX6CjJsyDmoRM4/s+y92Aq8dtcjUicrjalmOHNIN5XCgNKKgBmDJlCmvWrOHCCy/E5XLx+OOP8+Uvf5mSkhJiY2NJSUkJ/EV+9tlnExcXR15eHueeey4/+tGPePbZZ2lvbycrK4sHHniAV199ldjY2KB/YSONBe2oERERERGJNMXFxbz88ss8//zzZGdn4/V6qaio4KKLLuK2224zuzyJVPYUOPmL8KU/wa1lcM3LcMb1kDYGejpg52vw0nfhfybAny+CNQ8cN2wYl5XE4qm5ADz6YUXfOxvLoXkfXmssT9WOw2qBxSfnDuMXZ57i7CQAyuvbjAOZvvFnjWUmVTQ8BryfZt9a6OmElDxjN5Kc0DmTcwAj/BRDlaMDCP+OmoQsY7LQKEsz9a1dJlcjIocbldK/nyH9fVwoDTioAZgwYQKvv/46b731Ftdddx2FhYV4vV48Hg9tbW14vV68Xi+dnZ2B971eL1lZWVx++eWsWLGC/fv3893vfjfYX8+I5X+RizpqREREREQiz6WXXspnn33GokWLAEhKSuKKK64wuSqJCrZYKD4bLvoV/GALfOdDOPv/Qe508Hpg3xp489/gt6fDg2fC2/8FB9cf8Z/Lb51VBMCLGw9S1+I6dIdv7Fll6qm0E88ZRVlkR+HYMzB21ADsa2yn2+2BzGLjjijrqNnq66iZ3u/9NMafAYrPjapdPcPp7ElGULOmTF0ZftVO4+dKuO+osaQao89GW5r6/iwUkbAwpyiTvLT4Y24JsWAEwnOKMkNZVr8MaEfN4c477zzOO8+YP3rgwAEqKyupra2lvb0dl8uF3W4nMTGRnJwcSkpKyM4+yixbCQr/Hz6vempERERERCLS6NGjeeONN/jBD37A1KlTmTVrltklSbSxWCDvFOPt3NuheR/seN3osNmzGmq3G28f/g+k5MPki4y9NuPPYua4TE4fm87Gfc38de0efvSFycY5fRfp3+46GYAlp0Tn2DOA0SnxJMTa6Oh2s6+xnRJ/UNMQPR01XT0edlYb4+2m5fczqAnsp9HYs/6ampdKToqduhYXn+5pYv4EXS+rjpCOGlKMjsEMSysbmp0wJt3cekSkD5vVws+XTeX6v2044j7/9fOfL5uKzRp+LywYUlDTW2FhIYWFhcE6nQyQOmpERERERCKf1Wrlt7/9rdllyEiRPhbmXm+8tTfCrn8aoc2ut6ClEj591Hizp8KE87lj3Hz+dV8af/1oLzecM4GEtgOBoObppklYLXBhlI49A7BaLRRlJ7G9yklFXRslWf7RZ9HTUbOrtoUut4fU+BjGZCac+BNa66B6i/F+8TnDWls0sVgsnDUxh+c3HOD90roRH9T0uD2B7pTcMO+oIT6dLksccd4uWuv3A2PNrkhEDnPhtDwWTMhm1e76Psdz0+L5+bKpXDgtPF9UErSgRsxlOWZDl4iIiIiIiMgJJGbCqVcab92dUPGBEdrseB3aamHbC8zgBTbEx7C2+ySqHnuM4qqV+Oc6TLNWkDJuJjkp0Tn2zK8oxwhqyutb4ST/6LMK41WTUTD2yz/2bFpBWmD/8HGVv2fcjp4OyaOGr7AodM5kX1Czs46fLjnJ7HJMVdfqwuOFGKuFrHAfnWix0BKbQ1bXQbqaKs2uRkSOor2rh037mwG4Y+lJZKfYGZVijDsLx04aPwU1UeJQR41aakREREREosHmzZv57//+b2JiYnjyySfNLkdGkth4mPQF423pvcbOmp2vwY7XiK0v5SzbFqjaEni4BfjvmD/z0sTo36tUkm3sqamob4P0SYAFulqgrS4qgoqtB53AAPbTaOzZoC2YkI3VAjtrWqhs7iA/vR8dTFGq2tEJwKgUe1hfRPXriM+BroN4HApqRMLRa59V0erqYVxWIt9YUNS/Fx6EAavZBUhwHNpRIyIiIiIi0cDhcPDcc8/x6quvml2KjGRWK4yZDef/B9z4CW3f/ohnWXTEw2IsHs4b3Rr6+kKsOCcZgLK6NiPQShtj3BEl48+2+DpqTu5PUOM4ADtXGu8rqBmwjKQ4TvXtN/mgtM7cYkzmD2pyw30/jU934mgArK1VJlciIkfzzKf7Abhi1piICWlAQU308P2hU0ONiIiIiEh4WrduHZ999hmlpaXs3buXmpoaqqurOXjwIGVlZWzevLnP4xMTEwFISkoyo1yRo0rKP4lPxn4Lt7fvhQ+318qm1kyTqgqdot4dNQCZRcZtFAQ1PW4Pn1f1s6Nmw1/gvunQ0Wh83FgxzNVFp3MmGV1Y74/0oMYZWUENycYurriOWpMLEZHD7a5t5ZM9TdisFi6fWWh2OQOi0WdR4lBHjZIaEREREZFwNHfu3OO+qs9isdDT0xP42G435vTHxcUFju3evZulS5cyceLEwNvkyZOZPn06o0ZF/tglCX//2FrFM6UesF3HXTGPEmPx0OO18tOeb/LsC5U8lJgbtkt6g6Eoxwhq6lpctHR2k5JVAhXvQ0OZyZUN3e66Vlw9HpLtMYzLTDz2Ax0H4ZWbwes5dOz1W2HShZBWMPyFRpGzJ+dw71ulrNpVT7fbQ6xtZL6eOtBRkxoZ499i0o0/54mukR2wiYQjfzfNuZNzGJ0aIeGvj4KaKHFoR425dYiIiIiIyLENZKekzWbrcwvgdrvZtWsXu3fvZuXKlX0en5eXxznnnMNNN93EnDlzglOwSC9uj5c7X9kOwDPuc/nAfQrjrTXs8YymmiwswJ2vbOeCqbkRsWdiMFLjY8lOtlPf6qKivo1TMouNO6Kgo8a/n+bk/FSsx/v9ayzrG9IAeN3Gr4GCmgGZXpBGRmIsTe3dbNzXzJyi6O9KO5pDHTV2kyvpn/gs4895ak+9yZWISG9dPR5e2HAAgCtnjzW5moFTUBMlLL6eGuU0IiIiIiLhy2Kx8Ktf/Yq8vEMdBy6Xi+uuu+6Ix/oDmpiYo/+37fDQp7Kykr///e88//zzrFq1ipkzZwaxchFYV9FIle+V7wDVZFHtyQp87AWqHJ2sq2jkzJKso5whOhTnJFHf6qK8LtqCGmM/zbQTjT3LLAGLtW9YY7GB/9dC+s1mtbBwYg4vb67k/dLaERvU+H+uRMqr35Ozjd1UOd5G2lw9JNl1eVUkHLyzo4b61i5yUuycOznH7HIGbGT2VEahCNqLJCIiIiIyoi1fvpyvfvWrgbcrr7xyUOeprKzkww8/5E9/+hPf+c53SE9Px+v10tXVxeOPPx7kqkWgtqXzxA8awOMiVbFvT015fZsRWoAR1ET4iItDQU3q8R+YVgAzrz30scUGy+5TN80gneO7mPjezpE7RqvG11GTlxYZo88SMo29F6MtTdQ5o/vnnUgkefoTY+zZ5TMLiYnAUZKRV7EcV4T/u1BERERERPopNzeX+fPnc9111/HQQw+xfv16UlJSANi4caPJ1Uk0GpXSv1e79/dxkarYt6emvK4VMsYDFnA5ob3B1LqGwu3xsq3SGH02/UQdNQDdHcbtSV+EH2yBGdcMX3FRbuFEI6jZVumM+pDzaLxeb6CjJjdCOmpIyQUgyeKioSlyv+9FokmVo4P3S43A+4pZY0yuZnD6HdSsWrVqOOsIaGhooLS0NCTPFU0ONdQoqRERERERGYmKioqYMWMGXq+XsrLIX2wu4WdOUSZ5afEca6CDBchLi4/68U1F2ckAVNS3QWw8pPo6SRoi9/uuor6Vjm43iXG2wNd3TB437HrDeH/ON9VJM0Q5KfZAF9OHpSNv50lzezddPcYYvVGpkbGjhrgk2ixGYNtad8DkYkQE4LlPD+DxwhlFmRT5Ol8jTb+Cmj/96U+cc8453HjjjcNaTFNTE4sWLeLcc89VWDNA/tFn6qgRERERERm5/B01NTU1dHd3m1yNRBub1cLPl00FOCKs8X/882VTsR1vEX0U8HfUVNS3GbuisiJ/T80W39izqXmpJ/79O/Cp0T1kT4OxZ4aguuh3zqRRAIFXg48k/m6azKQ44mNtJlfTf86YbAA6GxXUiJjN4/Hy9KfG2LMrZ0dmNw30M6iJj4/HYrHw0EMPceWVV9LZGfxWzD179rBgwQI+++wzLBYLFi1dGRD/r5eCGhERERGRkcvb6z8EVVVVJlYi0erCaXk89LUZ5Kb1HVGUmxbPQ1+bwYXT8kyqLHTGZCRis1po73JT43RBZuQHNVsPGmPPpvVn7FnpP4zbCYvAFjuMVY0cZ/v21Hywqw63Z2Rd2PHvp4mYsWc+7fHG75nbUWlyJSKytryBA00dpMTHcFEE/zskpj8Puuaaa0hNTeVrX/sazz33HLt37+bJJ59k8uTJQSli5cqVfP3rX6euro6SkhLeeOMNiouLg3Lukcar0WciIiIiIhGvqamJ559/fsCf19bWxpQpU7jkkktIS+vHBVeRQbhwWh4XTM1lXUUjtS2djEoxxp1FeyeNX1yMlbGZiVTUt1Fe10puIKiJ3NFn/o6aAQU1ky8axopGltPHpJMSH0NzezefHWjm9LEZZpcUMoH9NGmRFdR0JYyGFrC0VptdisiI99QnRjfNJaflkxAXOZ15h+v3jpovfvGLrFq1irFjx7Jx40ZmzJjB3XffjcvlGvST19XV8e1vf5uLL76Yuro6zjvvPNatW6eQZhA0+kxEREREJPJt2rSJa6+9loKCAu64444Bf/5vf/tbtm/fzt13362gRoaVzWrhzJIsLjmtgDNLskZMSOPnn39fXt8GmSXGwQjtqPF4vGyv9HfUpB7/wU17oXY7WGww4fwQVDcyxNisLJxojNIaaePPqp2RGdR4k3MBiG1TUCNipqa2Lt7YanwfXjV7rMnVDE2/gxqA0047jc2bN3PNNdfQ0dHBv//7vzNx4kR+9atfUVtb2+/zlJaWcssttzBx4kQeffRRYmNjueuuu3jzzTfJyBg5rxoIJotvIrByGhERERGR8NHY2Mijjz7KlVde2a/HP/jggzz++ON0dnb2GWPWX9OmTRvw54jIwBX7g5q6tkOjzxrKI/LVk3sb22l19WCPsTIhJ/n4D/Z304ydC4mZw1/cCHL2JGOU1iubK3lp00HWljWMiDFo1Y4OIPJGn9nSjPFKCa6RFayJhJv/23SQLreHk/NT+9cVGsb6Nfqst9TUVFasWME111zDrbfeysaNG/npT3/Kv/3bv3H66aczf/58pkyZQl5eHikpKbjdblpaWti3bx/bt2/nvffeo6zMaAf2er0sW7aMe+65J2hj1EYqddSIiIiIiISPhoYGrrvuOl5//XV6enr6/Xnf/OY3eeSRR8jJyeGcc87h2WefHcYqRWSwinKMoKaivhUyfAGpywHtjZCUZWJlA+cfe3ZSXioxthO8nnfnSuN20oXDXNXI4/Fd0Cmra+PmpzYBkJcWz8+XTY3q3U/VTmNST6R11NgzCwFI7a43uRKRkcvr9fK0b+zZlbPHmFzN0A04qPE777zzWL9+PW+88QZ/+MMfeOONN1i/fj3r168PLLY/nP8VYRkZGVx22WXccMMNnH766YMt4ZgeeeQR7rzzThoaGpgzZw5//vOfKS4uZuvWrVx77bXs3r2b6667jnvuuSdQ6/vvv8/1119PXV0dP/3pT/nRj34U9LqGk/9XXDtqRERERETMl5GRwdq1a+np6RlQZ8ysWbP46U9/yh133MGePXt49tlnaW5u5o9//COjRo2iq6trGKsWkf4qzjY6T8rr2yAuEVILwHnQGH8WYUHNNl9QM/1Er0TudMKeVcb72k8TVP/YWsVPX9h6xPFqRyc3/G0DD31tRtSGNZHaUZOUbVwUzvA04PV6j3ktVESGz2cHHOyobsEeY+WSUwvMLmfIBh3U+C1evJjFixfT2dnJqlWr2Lx5M6WlpdTV1dHa2orVaiUlJYW8vDwmT57M7NmzmTVrFlbrgKau9VtZWRn/+Z//yUsvvUR2djZ33nknX//61/nnP//JsmXLWLx4MU899RQ33XQTK1as4Nprr6Wuro7ly5dzyy23cPXVV3PVVVdx+umnc+655w5LjcPBciipERERERERk1mtVi699FL+9Kc/cf7553PVVVdx3XXXnfDzbDYbv/jFL/oca2ho4Lvf/e4Rj/3Wt77F1772Nc4+++yg1S0i/VPs66jZ39hOV4+HuMziQ0HNmNkmVzcw/o6aE+6nKXsHPN3GTp7siSGobGRwe7zc+cr2o17O8WK8MPfOV7ZzwdTcqNwFVe0wdtTkRVhHTeooI6gZRROOdhfpSZFVv0g0eMrXTXPRtFzSEmNNrmbohhzU+MXHx3P++edz/vnmLpPbuHEjc+fOZcaMGQB84xvf4Mtf/jIrV67E4XDwm9/8hsTERO666y6+973vce211/LEE0+Qn5/PHXfcgcVi4Wc/+xmPPvroMYMal8uFy+UKfOx0OkPytR2PdtSIiIiIiISXW2+9ldtuu42ioiKAfgU1x3K0rpw///nP/PnPf+bMM8/kgQce4LTTThv0+UVkYEal2EmKs9HW5WZfYxsTMothz4fQWGZ2aQPi9XrZGghqTtBR499Po26aoFpX0UiVL6w4Gi9Q5ehkXUUjZ5ZEVrfWibR39eDsNMaDjo6woMaeng9AnMXNgbpq0pPGm1uQyAjT3tXDK5srAbhy9liTqwmO4WlrMdHUqVN555132LRpEw6HgwcffJALLriAzZs3M3fuXBITEwE45ZRT2L59OwCbN2/m3HPPDbQpzpkzh/Xr1x/zOe6++27S0tICb2PGmD8D79COGkU1IiIiIiLhoLi4OBDSDEV+fj4rV67k2Wef5d577+X6669n8uTJeL1evF4va9euZc6cOfzv//5vEKoWkf6wWCyBPTVldW2QWWzc0VhuYlUDt7+xA2dnD3E2KxNHpRz7gR437HrTeH/S4tAUN0LUthw7pBnM4yKJv5smKc5Gij1oryUPDVssTRYj3HTW7Te5GJGR57XPqmh19TAuK5G5xZlmlxMUEfZT8MSmTp3K5ZdfHth9U1RUxMcff8wvf/nLPv9Jslgs2Gw2mpqacDqdTJ06NXBfamoqlZWVx3yO22+/vc8OG6fTGRZhjYiIiIiIRJ+EhAQWLz7ywujnn3/Of/zHf/Dss8/S09PDbbfdRmVlpQIbkRApzk5m60EnFfVtkBOZQc3WSqObZkpeCnExx3kt74FPob0B7Gkw9swQVTcyjErpXydJfx8XSaqdRlAzOi0+Ine8OGzZZPQ46GhQUCMSas98anzfXTFrTET+/DiaqOuoWbduHa+88gofffQRzc3NXH311SxZsoSYmBjsdnufx8bHx9Pe3n7Eff7jx2K320lNTe3zFi7UTyMiIiIiMjKcdNJJPP3006xcuZKMjAy8Xi/33XdfnxeVicjwKco2OmrK61ohq8Q42BBZo8/8+2lOzj/R2LOVxu3E88EW+XsAwsmcokzy0uI51mVGC8b+ljlF0fGK8d4idT+NX5s9B4Ce5mO/2FtEgm93bSuf7GnCaoHLZxaaXU7QRF1Q8/e//52rrrqKM844g7S0NH7xi19QVlZGZmYmdXV1fR7b0tJCXFzcEff5j0cSf3KoyWciIiIiIiPL4sWL+eijj8jLy8Pr9XL//ffzwAMPmF2WSNQr9o0+q6hvg4zxxsHOZmhvNK2mgTq0n+YEL0Dd6dtPM0n7aYLNZrXw82XGlJfDwxr/xz9fNhWbNTpeMd5boKMmNTKDms6E0QB4W6pNrkRkZHnW101z3pRREfvz42iiLqjxeDzU1tYGPm5paQl0zaxduzZwvKKiApfLRWZmJrNnz+5z38aNGykoKAhp3UPl/+taOY2IiIiIyMgzceJEVq5cSWJiIl6vl9tuu41t27aZXZZIVCvOTgagvK4N4pIgJc+4I0LGn3m93kBQM73gOB01TXug7nOw2IyOGgm6C6fl8dDXZpB7WGdJZnIcD31tBhdOyzOpsuEV6R01niQjqIlprzG5EpGRo9vt4fkNBwBj7Fk0ibqgZuHChbzwwgvce++9PPnkk3zxi18kNzeXm266CafTyWOPPQbAXXfdxfnnn4/NZmP58uWsXr2at956i+7ubu65556jzoAOZ/5RfF611IiIiIiIjEinnHIKd999NwAul4tf/vKXJlckEt2KfB01DW1dONq7IdM3/ixCgppKRydN7d3EWC1MGp1y7Af6u2nGngkJGaEpbgS6cFoeq35yHn//1lxOLTSCs2vmjovakAYOBTW5EfqKeGua8XuT0KGgRiRU3v68lvrWLnJS7Jw7ZZTZ5QRVjNkFBNtll13G559/zn333UdVVRXTpk3jxRdfJDY2lkceeYSrr76aW2+9FavVynvvvQdAdnY29957L0uWLCE5OZn09HRWrFhh6tcxUOqoERERERGJDOvWraO6+tCYlI6OjsD7H374YeDFV/v27QPA7XbT2tpKcnLyCc9944038uCDDzJ9+nQeffTRIFcuIr0l22MYlWKntsVFeX0rp2cWwd5VERPUbDlgdNNMGp1CfKzt2A/076eZfGEIqhrZbFYLZ5ZkcfmsMWw+4GBteQM3m13UMPKPPstNSzC5ksGJyzB2YyR315tcicjI8fQnxr+PL59ZSKwtunpQBhzUfPDBB4N+sri4ONLT0xkzZgxJSUmDPs/xWCwW7rjjDu64444j7lu+fDllZWWsX7+euXPnkpWVFbjv+uuvZ/HixezYsYOFCxf26z9B4cQSaKkxtw4RERERETm+f/3Xfz3imP/f8+ecc84Rx/fs2UNaWhqxsbEUFRUxZcoU5syZw4IFC5g3bx42m63P4x944AHmzZsXcXs3RSJRcU4StS0uKurbOD2z2DjYUGZuUf20rbIf+2k6nbBntfG+9tOEzPwS43rVhr3NdHS5SYg7TpAWwSK9oyYpywhqMtwNJlciMjJUOTp4v9TYMx9tY89gEEHNOeeccygUGCSr1crUqVO59tpr+c53vkNCQuiS89zcXJYuXXrU+4qKiigqKgpZLcF0KKdRUiMiIiIiEq6GMqq4q6uLnTt3UlpayssvvwxASkoKS5cu5eqrr2bJkiVYrVYWLVoUrHJF5ASKspP5qLzR2FMzJrJGn/VrP03ZO+DxjXXLnhCiyqQoO4m8tHiqHJ18sqeRsyblmF1S0HW7PdS1ugCO2M0TKVJGGUFNpteBu7sLW6xeICEynJ779AAeL5xRlElR9vA0gZhp0KPPhvIfDLfbzdatW7nlllt45JFHeO211xg3btygzye9Rp8ppxERERERCUv33HMPcXFxfd6sVitWqxWLxRK4dbvd9PT00NnZSXt7O83NzTQ0NFBZWUl5eTlbt26lq6sLAKfTyVNPPcVTTz1Ffn4+N9xwAzfeeCOpqcd5hbyIBE2Jb09NRX0bnOrrqImAoMbr9bLloBOAk48X1JT69tNMVjdNKFksFuZPyOa59QdYXVYflUFNXYsLrxdibRaykiIz4MjMKaDbayPW4qa+7gDZ+cVmlyQStTweL09/uh+AK2dHXzcNDCKoGTt27KA7arxeL+3t7TQ0NASCnu3bt3PJJZfw6aefEhMTdStzQsf3e6KgRkREREQkPP34xz8Oynm6u7vZsmULb7/9Nn/5y1/Ytm0bAJWVldxxxx38+te/5o477uDmm2/uMxZNRIKv2BfUlNW1QsYM42BHI3Q0QUKGiZUdX22Li/pWFzarhal5xwh2PW7Y9abx/iTtpwm1+ROyjKBmd3TuP6nyjT0blRKP1Tq0yT1msdls1FkyyKUeZ+1+BTUiw2hteQMHmjpIiY/homl5ZpczLAacjOzZs2fIT9rR0cE777zDT3/6U7Zs2cKWLVt4/PHH+eY3vznkc49UgY4ajT4TEREREYlqsbGxzJgxgxkzZnDrrbeyfv16fvnLX/LCCy/g9XpxOBy89957/PCHPzS7VJGoV5Rt7Lfd09CGJzYJa3IutFYbXTUFM02u7ti2HDDGnk3ISSY+9hiB7oFPoL0B4tNg7NwQVicA80qyAdhW6aS5vYv0xMjsOjmWGqdvP02Ejj3za7Zlkeuup73hgNmliES1pz4xumkuOS0/avd2Wc140oSEBJYuXcp7771HTo7Rvvn000+bUUrUCOyoUU4jIiIiIjKizJw5k2effZY1a9ZwyimnMHr0aJ566qkh7xYVkRMbk5FAjNVCZ7eHKmcnZPrHn1WYW9gJbK00gpppxxt7tnOlcTvhArDFhqAq6W10ajwTRyXj9cLasuhbVu/vqIn0oKY1zgjUupsOmlyJSPRqauvija3VAFw1e6zJ1QwfU4Iav4yMDK666iq8Xi+bN282s5SIZ0H/CRMRERERGcnOOOMMPvnkE1544QUSExPNLkdkRIixWRmbZXy/VdS1QZYvqGkoM7GqE9t60B/UHGeflfbTmG7+BCMEWF0WfePPAh01qZEd1HTEjwLA46wyuRKR6PV/mw7S5fYwNS/1+C8wiHCmBjUARUVFADQ3N5tbSJRQQ42IiIiIyMgVGxvLmWeeaXYZIiNKsW/8WXl9a6+OmnITKzqxrQedAEw/1gWvxgqo2wEWG0xYFMLKpLd5JVkArN4dvR01eRHeUeNOygXA1lZjciUi0cnr9fK0b+zZVXPGmFzN8DI9qKmuNtqWUlOP8yoOOSGNPhMREREREREJveKcJADK69p6BTXh21FT1+Ki2tmJxQIn5R3jWkzpG8bt2DMhISN0xUkfc0uysFqgor6NyuYOs8sJqhpfUDM6wjtqLKlGUGPvUFAjMhw+O+BgR3ULcTFWLjm1wOxyhpWpQU1TUxN/+ctfsFgsTJ8+3cxSIt6hwWdKakRERERERERCpTjbF9TUt0FmiXEwjDtq/PtpirOTSLLHHP1Bpb79NJMvDFFVcjSp8bGcUpgOwOrd0TX+rMppBE+R3lETm25cOE7uqjO5EpHo9PSnRjfNkmm5pCVG9740U4Iat9vNe++9x6JFiwIdNV/+8pfNKCVqqKNGREREREREJPSKfEFNRX0rZBrj3WlvgI5m84o6jq0HjKDmmGPPOp2wZ7Xx/iTtpzHb/An+8WfRE9R4vV5qHC4g8jtqErIKAUjrib7xdCJma+/q4eVNlQBcOXusydUMv5AFNV/60pcoLi5mzJgxJCcns2jRIjZv3gzApEmT+MY3vhGqUqKSxddTo5xGREREREREJHSKc4wdNQeaOui0JkKSsVw8XLtq/B01x1zIXPY2eLohawJkTwhhZXI08ydkA7C6rAFvlLw6t7Gtiy63B4j8oCY1x9iZkUordEfXeDoRs72+pZpWVw/jshKZW5xpdjnDLmRBTVVVFXv27KGyshKXy4XX68Xr9TJmzBhefPFF7HZ7qEqJToGOmuj4S1tEREREREQkEmQnx5Fij8HrhX2N7ZAV3uPPth50AscJanb+w7idpLFn4WDG2AzsMVbqWlzsrm01u5ygqHYa+2myk+OIizF9ffaQZGXl0OGNA8DVdNDkakSiy9Of7APgilljsFgsJ3h05Av5T0N/kFBYWMhtt93Ghg0bmDJlSqjLiDr+P6qKaURERERERERCx2KxUJzj21NT1wqZxcYdjRUmVnV0jW1dHPQtpZ+an3rkAzxu2PWm8f5kjT0LB/GxNmaPN15JvipKxp9VO4ygJjfC99MApCXGUYPx++Os229yNSLRo6yulU/2NGG1wOUzC80uJySOsTUu+B588EFaWlpISUkhNzeXvLy8UD31iOBPFdVQIyIiIiIiIhJaRdlJbD7goLy+7dCemsYyc4s6iq0HjbFnRdlJpMYfZSnz/nXQ0Qjx6TBmbmiLk2OaPyGbVbvrWb27gWvnF5ldzpD5O2pyI3zsGRjX45qsmYz3VtNWf4AcswsSiRLPfGIEn+dNGTW0EYmOg8bfx5klkFYQpOqGR8iCmtNPPz1UTzUiqaNGRERERERExBz+PTXldW1wUviOPvPvpzn5aN00AKUrjduJF4AtZJeM5ATmT8gC4OPyBnrcHmJskT0uLJo6agBaYrOhC7oaD5hdikhU6HZ7eH6D8f10xawxgz/Rhr/AKzeD1wMWKyy7H2ZcE6Qqgy+yf7JLgEU7akRERERERERMUZRtjD6rqG/rNfos/IKabb79NNOPtZ+m9A3jVvtpwsrJ+WmkxsfQ4urhM19XVCQLBDVR0FED0BE/CgC3s8rkSkSiw9uf11Lf2kVOip1zp4wa+AncPfDZs/Dy942QBozbV35gdNiEKQU1UWIE7FMSERERERERCUtH3VHTVgedThOrOtIW30X+aUcLahoroG4HWGwwYVGIK5PjsVktnFlidNWsiYI9NYHRZ2kJJlcSHN2JowGwtlabXIlIdHj6k30AXDajkNj+dhB6PLBnNbz6I/jfyfDCdUc+xusOyxdR+CmoiRIWtKNGRERERERExAz+jpqm9m6a3PGQ5NtUEUYXhBzt3exrbAdgWv5RgprSfxi34+ZBQkYIK5P+WDAhG4DVuxtMrmTooq2jhlRjD3dce63JhYhEvipHB++X1gFw5ewTjD3zemH/J7Dy/8G9U2HFEvj0UWivN3atcVhng8V26MUUYUgDR6OEOmpEREREREREzJEYF0NeWjxVjk7K69uYmVlsdNQ0lkP+aWaXB8A2336aMZkJpCXGHvmAnb79NBp7Fpbm+YKa9Xub6OhykxBnM7miwYu2HTUxafkAJHUpqBEZquc+PYDHC3OKMgMvgujD64WqzbD1edj2f+DYd+g+exqcdDFM+xIUnQ2b/26MO/O6jZBm2X2QVhCir2TgFNREGS9qqREREREREREJtaLsJKocnVTUtzEzswT2fwyNZWaXFbDVF9QcdT9NpwP2rjben3xRCKuS/irOTiI3NZ5qZyef7m1k4cQcs0salFZXDy2uHiB6gpqEzEIAUrvrjYvIejW1yKB4PF6eWb8fgKsO76ap2e4LZ17o260al2z8vTXtMig5D2Lsh+6bcQ2ULDIen1kc1iENKKiJOhp9JiIiIiIiIhJ6xTlJrClr6LunprHC3KJ62XLQ2Jdz8tHGnu1+Gzw9kDURskpCXJn0h8ViYf6EbJ7fcIDVuxsiNqjxd9Ok2GNItkfHZcmUHCOoiccFLifEH+V7TEROaG15A/sbO0ixx3DRtDyo3wVbXzDCmbodhx4YkwCTFhudMxO/ALHH2XeVVhD2AY1fdPxEFCwW7agRERERERERMUtRdjIA5XVtcFqRcbAhfDpqth08TkeNfz/NZI09C2fzJ2Tx/IYDrCmrN7uUQatxGkHN6CjppgHITE/H4U0kzdIOLdUKakQG6elP9lNoqeVn+Z+T8Of/guoth+60xcGEC4xwZtKFYE82r9BhoqAmSvibKjX6TERERERERCT0inOMWfoV9W2HulJ6j2cxUUtnN+X1bQCcnJ/a906PG3a9abw/SWPPwtl8356aLQcdNLd3kZ4YZ3JFA1fl66jJi6KgJifFzkFvBmmWdjoa9pOQM9nskkQii+MgHZue45s7Hue39jKo8h23xkDxuUY4M3kJJKSbWeWwU1ATJfzjL9VRIyIiIiIiIhJ6xb6lxxUNbbjTp2MDaKsFVwvYU0ytbXulMfYsPy2erGR73zv3r4OOJohPhzFnhL446bfRqfFMGJXM7tpWPipv4MJpeWaXNGCBjprU6Alqkuwx1FmymMRBWusPcJwhTCLi11ID218yxprtW0sCcKoF3FixFS00wpmTlkNiptmVhoyCmihh8fXUKKcRERERERERCb3CjERibRa6ejxUdtoZk5gF7Q1GV03eqabWtsU39mzaUceerTRuJ14ANl0mCnfzS7LYXdvK6t2RGdRUOTqA6OqoAXDGZkEPuBoPml2KSPhqa4DPXzbCmT2rwOsJ3LXFdjLPdM5m+gXXcMU5M00s0jz6GzhKWA7NPhMRERERERGRELNZLYzLSmJ3bSvl9W2MySwJm6Bmm6+j5qhBzU7ffppJ2k8TCeZNyObxtXtZvTsy99RUO1xAdHXUAHTEjYIe6HEoqBHpo6MZdrwGW5+H8vfA6z50X8EsmPYltmecx7IV5cTFWPnxnFPMqtR0CmqihHbUiIiIiIiIiJirONsIairqWjk7sxgOrAuLPTX+jprphwc1jeVQv9PYAzDhfBMqk4GaW5yF1QLl9W1UOTrIS4usQVvVzujsqHEljoZ2sLRUm12KiPlcLcaLALY+D2Vvg7vr0H25pxhjzU6+FDLGA/C3F7cAsGRaLmmJsSYUHB4U1EQJ7agRERERERERMVdxTjJQQ3l9G2QWGwcbzA1q2rt6KKtrBeDkgtS+d/q7acaeGfVLmqNFWkIs0wvT2by/mdW7G7h8ZqHZJQ1ItHbUeJNzoR5i22vMLkUkNBwHobEMMksgrQC62mHXm0Y4s+tN6Ok89Nick3zhzJcge0Kf07R39fDypkoArpg9JpRfQdhRUBM1tKNGRERERERExEzF2UkAVNS3QXGJcdDkjprPq5x4vTA61c6olMMujvv300y+KPSFyaDNL8nyBTX1ERXUdPV4qG81gppo66ixpeUDkOCqM7kSkRDY8Bd45WbfjhkL5M+Auh3Q3XboMZklMO0yI6AZddIxT/X6lmpaXT2My0pkblHW8NcexhTURIlDHTWKakRERERERETMUJxjBDXldW2QWWQcNDmo2XLAGHs2Lf+wsWedDti7xnhf+2kiyoIJ2Tz4Xhmrd9fj9XqxBBYXh7faFuMV9nE2K5lJcSZXE1zxmQUApHTXg8cDVqvJFYkME8fBXiENgBcq1xvvpo01gplpXzJGnPXjZ9PTn+wD4IpZY7BaI+Nn2XBRUBMlDu2oEREREREREREzFPk6ag42d9CZcirxAK3V4GoFe7IpNW2tdAIw7fD9NLvfBk8PZE2ErBITKpPBmjEuA3uMldoWF2V1rUwYlWJ2Sf1S7TCCmtFp9ogJl/orOSsfj9dCjMUN7Q2QnGN2SSLDo7GsV0jTy5L/hdnf7Fc441dW18one5qwWoio7sDhong3SkTbX3AiIiIiIiIikSYzKY60BGMRckVbLCRkGnc0VZhW09aDvo6aw4OaUt9+msnqpok08bE2Zo3PAGD17gaTq+m/aqcR1ORG2X4agKy0ZBrw7YBqqTK3GJHhlHmUYN9iM0ZoDvD69DOf7Afg3Mmjom5v1WAoqIkymnwmIiIiIiIiYg6LxRLoqqmob4PMYuOOhjJT6unsdrOrthWA6b2DGnePsewZYJL200SieSXZAKzaXW9yJf3n76jJTUswuZLgy0mxU+M1wjOvs9LkakSGUWIm2HqNLrTYYNl9kFYwoNN0uz08v+EAAFfOHhPEAiOXgpooodFnIiIiIiIiIuY7tKem9dBIMZP21Hxe5cTt8ZKdHMfoVPuhOw6sg44miE+HMWeYUpsMzYIJRlDzUXkDPe6jjCEKQ4GgpvefxSiRnRxHtS+o6Wg8aHI1IsOo/D1wd0FKHvzrK/CDLTDjmgGf5u3Pa6lv7SInxc65U0YFv84IpKAmSgQ6y9RSIyIiIiIiImKaYl9HTXnvjhqTgpre+2n6jEzfudK4nfgFsGl9cSSaVpBGanwMLZ09gd/ncFfljN6OGnuMjWZbFgAdDQdMrkZkGO14zbg9aTkUnTXgThq/Zz41xp5dNqOQWJsiClBQEzX8/95STCMiIiIiIiJinuKcZADK68IgqDng20+Tr/000cZmtTC32AgGVkfI+LMaR/TuqAFos+cA0O3Q6DOJUh73oaB/ypJBn6ba0cl7O2sBjT3rTUFNlLD4hp+poUZERERERETEPP4dNeV1rXjNDmoqfUFNQeqhgw1lUF8K1hiYcL4pdUlwLJhojD+LlKCmKrCjJjqDGle8b3yTs8rcQkSGy4FPoL0e4tNg3PxBn+a59fvxeGFOUWbg70xRUBM9Ah01SmpEREREREREzOK/6OTs7KHJXmgcbKmCrraQ1uHqcVNa0wIYY7ICSt8wbsfNMy62ScSaV2IENZ/ubaKz221yNcfn8XipbYnuoMadnAdATHuNyZWIDJMdrxq3ExeDLXZQp/B4vDztG3t2lbpp+lBQEyW0okZERERERETEfPGxNgrSjR0c5W1xEJ9u3NFYEdI6Sqtb6XZ7SU+MDdRj3OEbWzNJY88iXUlOEqNT7XT1ePh0T5PZ5RxXQ1sX3W4vFguMSrGbXc6wsKYaQU18Z63JlYgMA6/30H6aKUsHfZq15Q3sb+wgxR7DRdPyglRcdFBQEyX8SwEV1IiIiIiIiIiYqzjHP/6sDbJKjIMhHn+25aAx9mx6QVrgmgGdDti7xnhfQU3Es1gszJ/gG39WFt7jz2qcRjdNdrI9aheH2zOMpeqJ3U3g7ja5GpEgq9tp/D1mi4MJiwZ9mqc/MbppLjk9n4Q4W7CqiwrR+ZNxBAp01JhahYiIiIiIiIgE9tTUt4FJe2r8+2lOzu813mz3W+DpgexJhwIkiWjzfePP1oT5nhr/fpq8KB17BpCcOZourw0rXmjV+DOJMjt93TRFZ4M9ZVCnaG7v4h/bqgG4ctbYYFUWNRTURAn/i2O8aqkRERERERERMVWxP6ipa+0V1JSFtIatvTpqAnb+w7hVN03U8HfUfHbQgaM9fLs4qn0dNaNTozeoyU6Jp5YM44OWanOLEQm2Ha8bt0MYe/Z/Gw/S1eNhal4q0wpSg1RY9FBQEyUsgZ4aERERERERETFTUU4yABX1bZDpH30Wuh013W4PO6paAA5dDHP3wK43jfcnXxSyWmR45abFU5KThNdr7H4IV9WODiC6O2pyUuzUetOND1qqTK1FJKicVXDwU+P9Qf794fV6eco39uzK2WMOjeSUAAU1UeJQR425dYiIiIiIiIiMdP6Omr0N7bgzioyDIRx9tqumlS63h5T4GMZmJhoH938Mnc2QkAGFc0JWiww/f1fNmjDeU1PtcAHR3VGTk2Knxmt01HgclSZXIxJEpSuN28LZkJI7qFNsOehgR3ULcTFWvnhaQRCLix4KaqKEMkgRERERERGR8JCfnkBcjJUut4cqa55x0HkQutpD8vz+sWfT8tMOvWrZf6Ft4hfAFhOSOiQ05vn21KwO4z011c7o76jJSrJT480EoKPxgMnViATRDt9+mslLBn0KfzfNkmm5pCXGBqOqqKOgJlr4/t3lUUuNiIiIiIiIiKlsVgtFWUZXza7WOIj37Ylp2hOS599a6dtPU9hrP03pG8at9tNEnTOLs7BaoKyujWpHp9nlHJW/rtwo7qixWS20xBmhWXezOmokSnQ6oeID4/0pFw/qFO1dPbyyyfieuGL2mGBVFnUU1EQJm+8VMgpqRERERERERMxX5Bt/VlHfDpnFxsHGspA89xZfR83J+b79NA1lUF8K1hiYsCgkNUjopCXGMr3ACOXCtasmENREcUcNQGf8KAC8Tu2okSix+y1wd0HWBMiZNKhTvL6lmhZXD+OyEplblBXkAqOHgpooYbX6gxqTCxERERERERERinOMoKa8vhUyS4yDIdhT0+P28HmVEyBw8Z7Sfxi34+Yd6u6RqDLPt6dmdRjuqWnp7Katyw1Ef1DjThoNgLW12uRKRIJk5+vG7RDGnj3jG3t2xawxgWvYciQFNVHCqo4aERERERERkbBxqKOmrVdHzfAHNWV1bXR2e0iKszHeN36Nnb79NJMuGvbnF3PM77Wnxhtm14b83TSp8TEkxkX5fqRUYydVfGetyYWIBIG7G0rfNN4f5NizsrpW1u1pxGqBy2cWBrG46KOgJkr4w0i3WmpERERERERETFeckwxAeV2voKZh+EefbQ2MPUszXrnc0Qz71hp3TtZ+mmg1a3wGcTFWapwuyurazC6nj2rnyBh7BhCXXgCAvacFutpNrkZkiPasApcDknKgcNagTuHvpjl38ihGR/GOqmBQUBMlbP7RZwpqRERERERkiB555BHGjBlDYmIi55xzDuXlRhfA1q1bmT17NhkZGdx6661h96ptkXBS7OuoqXJ00pk63jjYWDHsz+vfTzPNP/Zs91vg6YHsyYcCI4k68bE2Zo3LAGBNmI0/q/J11IyEi7SpaZm0e+3GBy3aUyMRLjD27CKw2gb86d1uD89vOADAlbPHBLOyqKSgJkocGn1mciEiIiIiIhLRysrK+M///E9eeuklduzYQUlJCV//+tdxuVwsW7aMmTNn8umnn7J9+3ZWrFhhdrkiYSsjKY6MxFgA9niNvRU4D0B3x7A+77ZKf1CTahzw76dRN03Um+/bU7NqV3gFNTW+oCZvBHTU5KTGU+01AjNatKdGIpjXCzv8Qc3SQZ3i7c9rqW/tIjvZzrlTRgWxuOikoCZK+IMat17RJiIiIiIiQ7Bx40bmzp3LjBkzGDt2LN/4xjfYvXs3K1euxOFw8Jvf/IaSkhLuuusuHn300WOex+Vy4XQ6+7yJjDT+PTW7Wuxg9wUnTXuG7fncHi/bKo3vtekFaeDugV3/NO7Ufpqo5w9qPipvCKvR+FX+0WcjoKMmJ9lOLf6gRh01EsGqNhsvLohNguKzB3WKZz41xp5dPrOQWJtiiBPRr1CU8I8+0+gBEREREREZiqlTp/LOO++wadMmHA4HDz74IBdccAGbN29m7ty5JCYmAnDKKaewffv2Y57n7rvvJi0tLfA2ZoxGXsjI499TU9HQfmjsWGP5sD1fRX0b7V1uEmJtxnPv/xg6myEhAwpnD9vzSniYXpBGSnwMzs6ewK6icODvqMlNSzC5kuGXk2KnxqugRqLAjteM2wnnQezAv3erHZ28t7MWgCtmFQazsqiloCZK+HKasHrFhIiIiIiIRJ6pU6dy+eWXc/rpp5Oens7atWv5n//5H5xOJ0VFRYHHWSwWbDYbTU1NRz3P7bffjsPhCLzt378/VF+CSNgozjE6asrrWkMS1Pgvzk/NTzVe0Fm60rhj4hfAFjNszyvhwWa1MLc4C4DVYbSnpioQ1NhNrmT49Q5qehyVJlcjMgQ7hzb27Ln1+/F4YU5RZuBFC3J8CmqihNWqHTUiIiIiIjJ069at45VXXuGjjz6iubmZq6++miVLlhATE4Pd3vciW3x8PO3t7Uc9j91uJzU1tc+byEhT7Bt9VlHfdiioaSgbtufzBzXT8n3fbzt9+2kmaT/NSLHAN/5s9e7wCWpqAqPPor+jJi0hljpLJgBdTQpqJEI17YGarWCxwaTFA/50j8fL076xZ1fNVkd1fymoiRL+HTUeJTUiIiIiIjIEf//737nqqqs444wzSEtL4xe/+AVlZWVkZmZSV1fX57EtLS3ExcWZVKlI+PO/iri8rg1vCDpqtviDmoI0IxBq2AXWGJiwaNieU8LL/AlGR82ne5ro7HabXA24etw0tHUBkJsW/TtqLBYLnfYcADxOjT6TCLXD100zbh4kZg740z8qb2B/Ywcp9hgumpYX5OKil4KaKGHzBzXaUSMiIiIiIkPg8Xiora0NfNzS0kJ7ezsxMTGsXbs2cLyiogKXy0Vm5sD/Ay8yUozNTMRigRZXD80JvlcVD1NQ4/F42V7pBHxBzU7f2LNx8yE+bVieU8JPSU4yo1LsuHo8bNh79NGUoVTrdAEQF2MlIzHW5GpCoztpNADWVgU1EqH8Y8+mDG7s2VOfGN00l5yeT0KcLVhVRT0FNVHC4t9Ro6BGRERERESGYOHChbzwwgvce++9PPnkk3zxi18kNzeXm266CafTyWOPPQbAXXfdxfnnn4/Npv+AixxLfKyNwgxj3FO5e5Rx0HEAujuD/lz7GttpcfVgj7EycVQylPrGnk2+KOjPJeHLYrEExp+tCoPxZ4H9NKnxWPwXr6KcN9noIIhrrwVdp5NI094Ie1cb709eMuBPb27v4h/bqgG4ctbYYFYW9bRJLkrYtKNGRERERESC4LLLLuPzzz/nvvvuo6qqimnTpvHiiy8SGxvLI488wtVXX82tt96K1WrlvffeM7tckbBXlJ3M/sYOdrUmMDMuBbpaoHkv5EwO6vP4x55NyUslpssBe9cYd2g/zYgzb0I2L2w8yOqyBrNLodq/n2YEjD3zi03Ph4MQ4+mETgckpJtdkkj/lb4BXg+Mng4Z4wb86f+38SBdPR6m5qUyrUD7CQci6jtqfvKTn7Bs2bLAx1u3bmX27NlkZGRw66234u2VbL///vucdNJJZGdn85vf/MaMcgdNO2pERERERCQYLBYLd9xxB3v37qWrq4sNGzZw+umnA7B8+XLKysp4/PHH+fzzz5k6darJ1YqEv+LsJADKG9ohs8g42FAW9OfZWmkENdMLUmH32+B1Q86UQ88pI4Z/T82WA804OrpNraXa0QEYHTUjRUZaKs1e4/uelmpzixEZqB2vGrdTBt5N4/V6A2PPrpw9ZsR00QVLVAc1n332GQ8++CD3338/AC6Xi2XLljFz5kw+/fRTtm/fzooVKwCoq6tj+fLlXH311axdu5YnnniCd99918TqB8bq+53UjhoRERERERlOubm5LF26lKysLLNLEYkIxTm+oKauDbJKjIPDsKdmq6+jZlp+2qGxZ5MWB/15JPzlpSVQnJOEx2ss9TZTtcPlq2nkBDU5KXZqvBnGBy2V5hYjMhDdHVD2jvH+IMaebTnoYEd1C3ExVr54WkGQi4t+URvUeDwevv3tb/PDH/6Q4uJiAFauXInD4eA3v/kNJSUl3HXXXTz66KMAPPHEE+Tn53PHHXcwceJEfvaznwXuO5zL5cLpdPZ5M1ugo8ZLny4hERERERERETFPcXYyAOX1rZBpXJ8IdlDj9XrZetC4NjEtLwl2/dO4Y5L204xU80uMPTVrTN5TU+00OmpGj6COmuzk3kGNOmokgpS/B93tkFoIeacO+NP93TQXTcslLTE2yMVFv6gNav7whz+wZcsWxo8fz8svv0xXVxebN29m7ty5JCYmAnDKKaewfft2ADZv3sy5554baMmaM2cO69evP+q57777btLS0gJvY8aMCc0XdRy2Xq1kymlEREREREREwkORr6NmX0M77nTfGLLG4I4+O9DUgaOjm1ibhcld26GzGRIyYcycoD6PRA7/+DOz99RUO4wdNSO3o6bK3GJEBmLHa8btlCUwwLFl7V09vLLJ6CC7crb518ojUVQGNa2trfz85z+nuLiYvXv3cu+997JgwQKcTidFRYdms1osFmw2G01NTUfcl5qaSmXl0dsTb7/9dhwOR+Bt//79w/41nYi11zePW0mNiIiIiIiISFjIS40nPtZKj8dLTaxvFEyQO2r8Y88m56YQu9s39mziF8BqC+rzSOQ4szgbiwV217YGwhIz+J979EgKapLt1OALapwKaiRCeNywc6Xx/pSlA/7017dU0+LqYWxmInOLNB53MKIyqHnhhRdoa2vj3Xff5c477+Sf//wnLS0t/PnPf8Zut/d5bHx8PO3t7cTExPS5z3/8aOx2O6mpqX3ezGbt9Tvp9iioEREREREREQkHVquF8Vm+PTXuUcZBxwHocQXtObb4gprpBb3200y+MGjnl8iTlhhr/HkA1pSZM/7M7fFS2zIyd9RUezMB6HFoR41EiAOfQHs9xKfBuPkD/vRnfGPPrpw9Bqt1YN04YojKoObAgQPMnTuX7GxjHmdMTAynnHIKzc3N1NXV9XlsS0sLcXFxZGZm9rnPfzxS2KwafSYiIiIiIiISjkpyjD01O1oSIC4ZvB5o2hu082+tNPbTzE1rgobdYI2FkkVBO79Epnm+PTWrd5sz/qyh1UWPx4vVYnSZjBRJ9hgcNqOjwO1QR41ECP/Ys4mLwTaw/TJlda2s29OI1QKXzywchuJGhqgMagoLC+no6OhzbO/evdx3332sXbs2cKyiogKXy0VmZiazZ8/uc9/GjRspKCgIWc1DpdFnIiIiIiIiIuGpKNvXUdPQDpn+PTXBGX/m9XoDo89mudYZB8fPh3jzp3+Iufx7ataU1eM14VpRtdMYe5aTYifGFpWXII+pK8HXPddabW4hIv3h9fbdTzNAz3xqdNOcO3kUo1NHTvdcsEXlT8mlS5eyfft2/vCHP3DgwAF++9vfsnnzZr70pS/hdDp57LHHALjrrrs4//zzsdlsLF++nNWrV/PWW2/R3d3NPffcw+LFi03+Svqvd1DjUVAjIiIiIiIiEjaKc3xBTV0rZBYbB4MU1FQ5Omls6yLGaiG35j3j4KSLgnJuiWyzx2cSF2OlytFJeX1byJ+/yrefJncEXrj1pOQCENteCx6PydWInEB9KTSWgS0OJpw/oE/tdnt4fv0BwBh7JoMXY3YBwyErK4vXX3+dH//4x/zoRz8iLy+PZ555hjFjxvDII49w9dVXc+utt2K1WnnvvfcAyM7O5t5772XJkiUkJyeTnp7OihUrTP06BqL36D+PdtSIiIiIiIiIhA1/R01FfRsU+4OasqCc27+f5vQcC7Z9vkkhkyLnhacyfOJjbcwcm8Ha8gbW7K4PjOALlRpfR03uCNpP4xebmoenzoKVHmPvR/Ios0sSObYdrxq3RWeDPWVAn/rOjlrqW7vITrZz7hT9OR+KqAxqAObPn99nlJnf8uXLKSsrY/369cydO5esrKzAfddffz2LFy9mx44dLFy4kOTk0P4FNhS9d9QopxEREREREREJH8XZxvWFGqeLztQi4iFoHTXbfEHNF1O2g8MNOVMOjVeTEW/+hCzWljewencD/3Lm+JA+90juqMlKTaSeNEbRDC1VCmokvO143bgdxNizpz8xxp5dPrOQ2BE24jDYRuSvXm5uLkuXLu0T0vgVFRVx0UUXRVRIA2DpvaNGSY2IiIiIiIhI2EhLjCUrKQ6ASmuecbAhOB01WyudAMzr+cQ4MOnCoJxXosP8CdmAsacm1NeLavxBTVpCSJ83HOSk2KnxphsfOKtMrUXkuJxVcPBT4/3JAwtqqh2dvLezFoArZhUGu7IRZ0QGNdHK31VjxoI4ERERERERETk2/56aXd05xgHHfujpGvJ5txx0EEMPYxpXGwcmaz+NHDK9II0UewzOzh62VTpC+tyBjpo0e0ifNxxkJ9up9mYaH7QoqJEwVrrSuC2YBb7dSifi9nhZW9bAf726DY8XZo/PoDjEoxWjkYKaKOKffuZWUCMiIiIiIiISVvx7aj5vTYTYRPB6oHnfkM5Z6+ykrsXFbGspMV1OSMyCwtnBKFeiRIzNyhnFxkSZ1bsbQvrcgR01qSOzo6bWm2F80FJtbjEjmD9QeGnTQdaWNWgK0dEExp4t7dfD/7G1igW/eoerH/6I17YYf7ZLa1r5x1YFkkOloCaKWH3jz/QzR0RERERERCS8+F9tXF7fDpnFxsHGoY0/2+LbT3NZ8hbjwMQvgNU2pHNK9FkwwR/U1IfsOb1eb6+OmpG3o8YYfeYPanQB2wy9A4Wbn9rE1Q9/xIJfvaNAoTdXC1S8b7zfj6DmH1uruOFvGwLf237Ojm5u+NsG/doOkYKaKBIIapTUiIiIiIiIiIQVf0dNRX1br6CmfEjn3HrQ2E9zFhuMA9pPI0fh31PzyZ5GOrvdIXlOZ2cPHb7nyk0doUENRlDjVVATcscKFKodnQoUetv9Fri7IGsCZE867kPdHi93vrKdo1119h+785Xt6loaAgU1UcS/o8aj0WciIiIiIiIiYaXEt6OmvK4Vb5CCmi0HHRRZqhjVtR+ssVBy3lDLlCg0YVQyo1LsuHo8bNjXFJLnrPZdIE9LiCUhbuR1eWUnxwU6ajwOhQKhpEBhAHa8ZtxOXgK+BoBjWVfReETw1ZsXYy/VuorGIBY4siioiSL+7yf9oBEREREREREJL2MyE7FaoK3LTUviGONgw9BGn22rdLDI6uumGT8f4lOHWKVEI4vFEuiqCdX4s2rffpq8ETj2DMAeY6M1zvg1V0dNaClQ6Cd3N5S+abzfj7FntS3H/jUdzOPkSApqoog6akRERERERETCkz3GxpjMRAD2W/KNg0PoqKlvdVHl6OR8m3/s2UVDLVGi2LwS/56ahpA8X43vQvnoETj2zM+TlAtATEc99HSZXM3IoUChn/asApcDknKgcPYJHz4qpX/fy/19nBxJQU0UCeyoUU4jIiIiIiIiEnb8e2p2dhuvtKd5n/Gq5kHYetBBKq3Mtu40DkzWfho5Nn9HzWcHmnF2Du7P3ED4OxpGakcNQFxqDl1e39i31hpzixlBFCj0087XjdtJF4L1+OMJe9we3vq8+riPsWB8v88pygxSgSOPgpoo4g9qNPpMREREREREJPwUZycDsN2ZCDEJ4HUbYc0gbD3o4BzrZmx4IOckyBgfxEol2uSnJ1CcnYTHCx+XD//IJ//os5HcUZOTmkAtxp4aWo5/kVuCZ05RJnlp8Rxv40p8rJWT80fwqEivF3b4gpopFx/3oY72bq5d8QmPrtoTOHb4r63/458vmxqY+CQDp6Amith8v5safSYiIiIiIiISfopzjI6a8oYOyCw2Dg5y/NnWg85DY8/UTSP9MG+Cf/zZ8O+pqXZ0ACO7oyYn2U6N1x/UaE9NqNisFn6+bOpxH9PZ7eHyP6yhor4tRFWFmarN4DwAsYlQfPYxH1Za08Ly36/iw131JMTa+P1XZvCHr80g97Dv69y0eB762gwunJY33JVHtRizC5DgCYw+85hciIiIiIiIiIgcodg3+qyivg0Ki6B2GzSUwcQLBnyu7QcauMe62fhA+2mkH+aXZPO3j/aFJqhxugAYPYKDmuyUOAU1JrlwWh4PfW0GN/19E13uQxdK89Li+eoZY/nL2r2U1rSy/HeruPfK0zh/6mgTqzWBf+zZhEUQm3DUh7y5rZofPr2Jti43BekJPHzNLKb6upAumJrLuopGals6GZVijDtTJ83QKaiJIod21KijRkRERERERCTcFOcYo8/2Nbbjnl6EDQbVUdPU1kV+y2ZS49rxJGRhLZwV3EIlKp1ZkoXFArtqW6l1djJqGMeSqaNGHTVmO2fyKMC4RvrTJScxvSAtEChcMWsM33tyA5/saeK6v3zK98+bwA/OnzRywoYdrxm3k5cecZfH4+WBd3fzm3+WAjC3OJPff2UGWcn2wGNsVgtnlmSFpNSRRKPPoojV97vpVlAjIiIiIiIiEnZGp9pJjLPh9nhpsI8xDg4iqNla6WCR1Rh7Zp30hRMughYBSE+MY1p+GgCry4avq6az201TezcAuSN5R01K76BGO2pCbfP+ZrrcXrKT7XxrYRFnlmQFgphRqfE8+a25fH3eeAB+985uvrHiE5rbu0ysOESa9kDNVrDYYNLiPne1uXr43pMbAiHNv545jr9+84w+IY0MHwU1UcTm66jxKqgRERERERERCTsWi4Ui3/izfeQaBxvLBnyerQedgaCGSdpPI/13aE9Nw7A9R42zEzAWtqclxA7b84S7PkGNs9LcYkagj8obAaMjxGI5slMm1mblP5afzH1XnkZ8rJX3S+tY9sAqtlU6Ql1qaO3wjT0bNw8SMwOH9zW0c9lDa1i5tZpYm4Vffmk6d14yjVib4oNQ0a90FPGPPnNrR42IiIiIiIhIWPIHNTu7so0DzfvA3T2gc9Tu2UKxtRq3JQZKzgt2iRLF5pcYf+7W7K4fthf6VjuMoCY3Nf6oF8hHipwUO9UYF8K96qgJuY/KjTBybvHxR3R98fQCXrhhPmMzE9nf2MGXHlzDCxsOhKJEc/j300xeEji0Znc9y3+/ih3VLWQn23nq23O5as5YkwocuRTURBGrVTtqRERERERERMKZf0/NVmcSxMSDpwcc+wd0jpzKdwFwjp4L8alBr1Gi1+zxmcTZrFQ6OqmobxuW56j2ddTkjuD9NACZiXHUkg6AVztqQqqz282GfU3AiYMagKn5qbxy4wLOnZyDq8fDj57ZzM9e2kpXT5S9Gr69EfauNt6fsgSv18tjqyv4lz+vo7m9m1MK03jl+/OZOS7z+OeRYaGgJor49115PApqRERERERERMJRsa+jpqyhAzKKjIMN/d9T4+joZmbnRwDYT15ygkeL9JUQZ2PGuHQAVpcNz/iz3h01I1mMzUpPwmgArC4ndA1PMCZH2ry/GVePh+xkOyU5Sf36nLTEWB7919ncvGgiAH9Zu5erH/4oMMovKpS+AV4PjJ6GK2UMtz33GXe+sh23x8ulpxfwzHfOJC8twewqRywFNVHEP/pMOY2IiIiIiIhIeCr2XTQsr2uDrBLjYGP/g5qdFXuZaTEWPSdOuzjo9Un06z3+bDhU+YMaXfAlITmdNq9vEbvGn4XMifbTHIvVauGHF0zi0X+dRUp8DOv3NnHx71axrqJxuEoNrZ2vAdBatJgr//gRz64/gNUC/770JH5zxanEx9pMLnBkU1ATRQI7ajT6TERERERERCQs+XfU1Le6cKWOMw4OIKhp3foGMRYPB+OKIGPccJQoUW7+RF9QU9aAexhe7evvQMhNtQf93JEmJzWeaq9vjJTGn4VMf/fTHMuik0bzyo0LmJKbQl2Li688/BGPra4Ytr1OIdHdAbvfBuCGT3PZtL+ZtIRYHv/GHK5bWDyi90mFCwU1UcSmHTUiIiIiIiIiYS0lPpacFOMCdm1sgXGwsazfn5+2/y0AqkefE+zSZIQ4pSCNFHsMjo5utlc6g35+ddQckpNip9abYXygjpqQGOh+mmMZn53EC9+dx/JT8+nxeLnzle384OlNdHS5g1VqaJW/D93tVHqz+LA1n4mjknnpe/NZODHH7MrER0FNFNGOGhEREREREZHw5++q2evNNQ70t6PG3c3klo8BsEy+cDhKkxEgxmbljGKjy2N1WfDHnwU6atJG9o4aMIKaGtKND5yVptYyUgxmP82xJMbFcP9Vp/Gzi6dis1p4aVMllz64mr0NkbVvqMftYcObfwPgTfdMLpiay4vfm8/47KH9+khwKaiJIlZfUjMcbasiIiIiIiIiEhz+i4efu4wRVDTtBXfPCT+vo2wVybTR4E1h7ClnDWeJEuXmTzD+7K0O8p4at8dLbYsLgDwFNeQk26lRR01IDXY/zbFYLBa+saCIJ687g+xkOzuqW1j2u1W8u6N2yOcOhaa2Lr7+57WMqX8fgORTl/PHr80k2R5jcmVyOAU1UcS/o0Y5jYiIiIiIiEj48nfUfOZMApsdPN3g2H/Cz3NsegWAj2yzyE5NHNYaJbr5g5pP9jTi6gneKKf6Vhdujxeb1UJ2snbU5KTYqdGOmpAa6n6aYzmjOItXv7+A08em4+zs4RuPf8J9b5WG9WSjndUtXPL71XSUf0yOxUl3bAqXf+mqwIv9JbwoqIkiNot21IiIiIiIiIiEu+LsZADK6jsgs8g4eKLxZ14vCRVvArAvW900MjQTRyWTk2Kns9vDhr3NQTuvfz/NqBR7YJfySKaOmtAK1n6aY8lNi+fpb5/Jv8wdh9cL9721i+v+8imO9u6gP9dQ/WNrFZc+uJp9je1clrQZgNgpF4It1uTK5FgU1EQRq+93U0GNiIiIiIiISPgq8o0+q6hvw9vfoKZ+F2kd+3F5Y/AWnzfMFUq0s1gszC8xLmSvCeKemmpfUDM6VWPPwN9Rk2580KIdNcMtmPtpjiUuxsp/fXEa//PlU7HHWHlnRy3Lf7+Kz6ucw/J8A+XxeLn3n6Vc/7cNtHe5mVecyZUpnxl3TllqbnFyXApqooh/9Jl21IiIiIiIiIiEr7GZidisFjq63bQljTUOniioKV0JwMeek5gyPm+YK5SRYJ5v/NmqIO6pqXZ0ANpP45eTYqcaY/SZt6Ua9OLqYRXs/TTHc/nMQp6/YR6FGQnsbWjn0gdX89Kmg8P6nCfS6urh+r+t5/63dwFw7fzx/GV5OramcrDFwYTzTa1Pjk9BTRTxt5TqZ76IiIiIiIhI+Iq1WRmbaeyYqYkpNA6eIKhx7/gHAG95ZjAtP21Y65ORwb+n5rMDDlo6gzO6qdrpAtRR45eWEEuT1Rh9ZunphM5mcwuKcsO1n+ZYphWk8cqNCzhrUg6d3R5ufmoTd76yjW63JyTP39vehja+9OBq3txeQ5zNyj2Xn8LPl51MzC4j5KfoLLCnhLwu6T8FNVHEoo4aERERERERkYhQnG2M5Sn3jDYONJQd+8HtjVgPfAzA5oS5jNJFcAmCgvQExmcl4vZ4+djXiTBU6qjpy2KxkJqcQpPX2EulPTXDZ7j30xxLRlIcj319NjeeOwGAx1bv4asPf0xtS2fIavhwVx3LH1hNaU0ro1LsPPWduVwxa4xx547XjFuNPQt7CmqiiM3X0acdNSIiIiIiIiLhrcgX1GzvNLoaaNoDHvfRH7z7LSxeNzs8Y8gqnBiaAmVEmB/k8WfVTuPidK6CmgBjT43RVYNTe2qGSyj20xyLzWrhx4sn86d/mUmKPYZ1expZ9rtVrN8bnAD0WLxeL498WM6//nkdjo5uTh2TzivfX8CMsb4/by3VcPBT4/1JFw1rLTJ0CmqiiH9HjYIaERERERERkfBWnGO8wn6TM9HYHeDpBseBoz94pzG65m3P6Uwr0NgzCR5/ULOmLEhBjcMX1KjrKyAnuVdQo46aYRPK/TTH8oWTc3npxvlMHJVMjdPFVX/6iL+u3YN3GK7Vdna7ueXZzfzitc/xeOGyGYU8/e25fccO7nzduC2YBanabRbuFNREEavVH9SYXIiIiIiIiIiIHJe/o6a8oRMyxhsHG48y/szdDbvfBuBt9wym5aeGqEIZCc4szsJigdKa1iGPavJ6veqoOYo+HTUtVeYWE8VCvZ/mWIpzkvm/781n6fQ8ut1e7nhpG7c8u5nO7mN0TA5CtaOTK/+4lhc2HMRmtfCzi6fyP18+hfhYW98H7vAFNVOWBO25ZfgoqIkivpxGO2pEREREREREwpx/NM/+xnbcGcXGwcbyIx+4dw24HDR4U9nkncD0QnXUSPBkJMVxsi/8W7O7YUjncnR009ltLFEfrY6agOxkOzUoqBlOZu2nOZYkewwPfOV0/m3JSdisFl7YcJDLHlrD/sb2IZ97/d4mlj2wis0HHKQlxPL4tXP4xoKiI7uIXC1Q8b7x/pSLh/y8MvwU1EQRmy+pGY52OhEREREREREJnpwUO0lxNjxeaEn0LX1urDjygaX/AOAd92lkJMVrpJQE3fwSY/zZ6iHuqfF302Qkxh75yv4RrG9HjUafDQcz99Mci8Vi4VtnFfPXb84hKymObZVOLv7dKt4vrRv0OZ/5ZD9X/+kj6lpcTB6dwss3zmfBxOyjP3j3W+DugswSyJ406OeU0FFQE0X8yak6akRERERERETCm8ViCeypqbT6dgc0HDb6zOsN7Kd5yzODkwvSTNu9INFrXmBPTcOQXvxb5d9Pk5YQlLqihUafDb9w2E9zLPNKsnnl+ws4dUw6jo5uvv7YOh54ZxeeAVy/7XZ7+I+Xt3Hb85/R5faw+OTRvPDdeYzLOk4oFRh7thTC7NdEjk5BTRSxWbSjRkRERERERCRSBPbUeHKNA4ePPqvfBU0V9FhiWeWZzvQC7aeR4Js9PoM4m5WDzR3sbRj8aKYaf1CTag9WaVFBHTXDL1z20xxLfnoCz3xnLlfPGYvXC//zZinf+dt6nJ3dJ/zcxrYurnl0HSvW7AHgh+dP4qGvziTJHnPsT3J3w643jPenLA3CVyChoKAmivh31Hg0+kxEREREREQk7BX7RvRs6cg0DjRVgKfXwulSo5vms5hptJHAtHztp5HgS4yL4fSx6QCsGsL4M3XUHF1O8mFBjSd4S+Ul/PbTHIs9xsbdX5rOry6bTlyMlX9ur+GSB1ZTWtMCGBOS1pY18NKmg6wta8Dt8bK90snyB1axtryBpDgbf/yXmdx8/kSs1hN0yOxdDZ0OSMyGwtkh+OokGI4TvUmk8X+TavSZiIiIiIiISPjzjz7b2JwM1lhjn4DzIKSPNR6w09hP80rnqQBMK1BQI8Nj/oRsPq5oZE1ZPV+bO25Q56hx+jtqtEept+wUO/Wk4fZasOGGtnpIGW12WVEjHPfTHM+Vs8dyNv8gvgAAbDtJREFUUl4q1/91PRX1bXzx96v5yhljee2zqkDYCZCeGEu7y02X28PYzEQevmYWk3NT+vckO14zbidfBFbti4oU6qiJIlaNPhMRERERERGJGMW+0WdlDZ2QMd446B9/1t4I+z8C4M3u00lLiKUwQ50KMjzm99pTM5DdGb35LzLnpSmo6S0pzkZcbBz1+IJW7akJqnDeT3MspxSm88r3FzB/QhbtXW4e+bCiT0gD0NzeTZfbw5TcFF6+cX7/Qxqvt+9+GokYCmqiyKEdNUpqRERERERERMKdf0dNQ1sX3WnjjYMNZcbtrn+C10NzykQOksP0grSIuQgpkefUwjSS7TE0t3ezvco5qHP4O2pGK6jpw2KxHLanRkFNMIX7fppjyUq28+d/nU1S3PE7Xhwd3aTEx/b/xFWbwXkAYhOh+JyhFSkhpaAmivhHnw32lQ8iIiIiIiIiEjpJ9hhG+xavN8UXGgf9HTW+/TSbEuYCcHJBasjrk5EjxmbljCJjV9LqQe6pUUfNsRlBjW8XlYKaoImU/TTHsmFfM21dx99ZVOXoZF1FY/9PutPXTVNyHsSqCzOSKKiJIv49Um511IiIiIiIiIhEhOJsY0/NQWu+caCxAnq6YPfbALzmOg2A6dpPI8PMP/5sdVnDgD+3o8uNo6MbgNHaUXOEnGQ7Nd5044OWalNriSaRtp/mcLUtnSd+0AAeBxzaTzPl4kFUJGZSUBNFbFbtqBERERERERGJJEW+i4tl7lHGgcYy2LcWXE68STm83JAHwLR8BTUyvPxBzbqKBlw9x3+V/+GqfWPPEuNspMbHBL22SJedEqfRZ8MgEvfT9DYqpX+hZn8fR9MeqNkKFhtMWjz4wsQUCmqiiNWi0WciIiIiIiIikaTYt6fms3bfWKTGisDoGkfhubh6ICU+hnFZiWaVKCPEpNHJZCfb6ez2sHFf84A+t9o39iw3NT4iL5gPt5zkeGrwBTVOBTXBEqn7afzmFGWSlxbPsb5jLBijBOf4xhKe0E5jZCZjz4TEfn6OhA0FNVEkENRo9JmIiIiIiIhIRCj2ddR82pwC1hhwu2DzUwBsSz4TgJPzU3XxW4adxWJhXolxwXvNAPfUVDs7AMjVfpqj6rujRqPPgiHS99OAMR3p58umAhwR1vg//vmyqYEpSicUGHu2NCj1SWgpqIki2lEjIiIiIiIiEln8O2rKGzvxpo8zDnY2gy2O97qnAdpPI6GzwDf+bNVAgxqHCzA6auRIRlCj0WfBFOn7afwunJbHQ1+bcUTImZsWz0Nfm8GF0/L6d6L2Rti7xnh/ypIgVymhoKGRUcSfriqnEREREREREYkMhRkJxNosdHZ7cKWOJ76xzHfHbNZXG8vZpymokRCZN8HoTNh8wEFLZzcp8bH9+rxqhzpqjscIatKND9rroccFMXZTa4p0kb6fprcLp+VxwdRc1lU0UtvSyagUY9xZvztpAErfAK8bRk+DjPHDVqsMH3XURBH/DyW3dtSIiIiIiIiIRIQYm5Wxmcb+mY6OjsBx7941nFT9fwCcnK+gRkKjMCORcVmJuD1e1lU09vvzqp2+HTUKao4qOzmOJlLo8vpeM99aY25BUSDS99Mczma1cGZJFpecVsCZJVkDC2kAdvrGnk1WN02kUlATRWy+303tqBERERERERGJHEXZyeTSQHrN2sAxC17utDxCcVwzxdmRO9ZHIs983/iz1bsb+v051Q5fUKPRZ0eVnWwHLL3Gn2lPzVBEw36aoOrugN1vG+9rP03EUlATRay+jhqPOmpEREREREREIkZJThJF1mos9P3/fIzFw8KsFqwDfWW1yBDML/EHNf3fU6OOmuOLj7WRGh9DDdpTEwzRsp8maMrfh+52SC2EvFPNrkYGSUFNFAkENcppRERERERERCJGUXYSFZ5cPIddpunxWkkrnGxSVTJSnVlidCjsrGmhrsV1wsf3uD2BxymoObY+e2qcCmqGIpr20wRFYOzZRaBfj4iloCaK+IMat0afiYiIiIiIiESM4pxkqsniV7E3gMUGgBsrP+35JuPGTzS5OhlpMpPiODk/FYA1ZSfuqqlrdeHxQozVQnaSfbjLi1hGUJNpfKCOmiGJtv00Q+Jxw86VxvsaexbRFNREkcCOGrXUiIiIiIiIiESMIt8Omj+1zqfzxk14rnmFCzwP8Iz7XKYXpplcnYxEh/bUnDioqfLtpxmVYteYvuPITrZrR00QaD/NYQ58Cm11YE+D8QvMrkaGQEFNFLEERp8pqBERERERERGJFNnJcaTEx+D1wt7uDCpSZlDelU58rJXibO1fkNCb5xt/tnp3A94TXGeqcWg/TX8YHTX+oKbS3GIimPbTHGbHq8btpC+ALdbcWmRIFNREEZvvVQtuj8mFiIiIiIiIiEi/WSyWQCBTUd/K1oMOAKbmpRJj06UbCb0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",
      "text/plain": [
       "<Figure size 2000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "plt.subplot(1,2,1)\n",
    "plt.plot(mse)\n",
    "plt.xlabel('迭代次数', fontsize = 25)\n",
    "plt.ylabel('J(θ)', fontsize = 25)\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "h_price = h_price.reshape(-1)\n",
    "plt.plot(label_mat, marker = 'o', label = '真实房价')\n",
    "plt.plot(h_price, marker = '.', label='预测房价')\n",
    "plt.xlabel('样本序号', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize=25)\n",
    "\n",
    "plt.legend(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 总结\n",
    "\n",
    "1、查找数据集\n",
    "\n",
    "2、确定模型类型\n",
    "\n",
    "3、确定代价函数\n",
    "\n",
    "4、利用梯度下降计算代价函数的最小值（模型的最佳参数）\n",
    "\n",
    "\n",
    "\n",
    "### 1. 数据准备\n",
    "- 加载数据集 D\n",
    "- 将数据集 D 划分为训练集 (X_train, y_train) 和测试集 (X_test, y_test)\n",
    "\n",
    "### 2. 数据预处理\n",
    "  - 对训练集 X_train 进行预处理（例如标准化、对类别变量进行编码）\n",
    "\n",
    "  - 对测试集 X_test 进行与 X_train 相同的预处理操作\n",
    "\n",
    "### 3. 模型选择与初始化\n",
    " - 选择模型 M（例如随机森林、逻辑回归等）\n",
    " - 使用初始参数初始化模型 M\n",
    "\n",
    "### 4. 模型训练\n",
    " - 在训练集 (X_train, y_train) 上训练模型 M\n",
    " - 对每次训练迭代执行以下操作：\n",
    "   模型 M 对训练集 X_train 进行预测\n",
    "\n",
    "   计算损失（预测值与真实值之间的差异）\n",
    "\n",
    "   优化模型 M 的参数，以最小化损失\n",
    "   \n",
    "   可选：如果验证集得分不再提升，执行提前停止操作\n",
    "\n",
    "### 5. 模型评估\n",
    "- 模型 M 在测试集 X_test 上进行预测\n",
    "- 使用评估指标（例如准确率、F1 得分、均方误差）评估模型性能\n",
    "\n",
    "### 6. 模型优化（可选）\n",
    "- 如果模型性能不令人满意：\n",
    "- 调整模型 M 的超参数（例如使用网格搜索或随机搜索）\n",
    "- 使用更新后的超参数在 X_train 上重新训练模型 M\n",
    "- 在测试集 X_test 上重新评估模型性能\n",
    "\n",
    "### 7. 模型保存（可选）\n",
    "- 保存模型 M 以便将来使用（例如保存为 model.pkl）\n",
    "\n",
    "### 8. 部署与监控（可选）\n",
    "- 在生产环境中部署模型 M\n",
    "- 随时间监控模型性能\n",
    "\n",
    "### 注释解释：\n",
    "- 每行代码对应的注释解释了其作用，帮助理解训练过程的关键步骤。\n",
    "- 从数据准备、预处理到模型训练、评估和部署，这些注释涵盖了模型训练的完整流程。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2 使用正规方程法\n",
    "\n",
    "$$\n",
    "\\theta=\\left(X^{T} X\\right)^{-1} X^{T} y\n",
    "$$\n",
    "\n",
    "Matric.T : 矩阵转置\n",
    "\n",
    "Matric.I : 矩阵求逆\n",
    "\n",
    "linalg.det(Matric) : 求矩阵对应行列式的计算值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2.1 定义正规方程函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def standRegres(xArr,yArr):\n",
    "    xMat = np.mat(xArr)\n",
    "    yMat = np.mat(yArr)\n",
    "    xTx = xMat.T*xMat\n",
    "    if np.linalg.det(xTx) == 0.0:\n",
    "        print (\"This matrix cannot do inverse.\")\n",
    "        return\n",
    "    W = xTx.I * (xMat.T*yMat)\n",
    "    return W"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2.2 执行正规方程函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[145.  ],\n",
       "        [110.  ],\n",
       "        [ 93.  ],\n",
       "        [116.  ],\n",
       "        [ 65.32],\n",
       "        [104.  ],\n",
       "        [118.  ],\n",
       "        [ 91.  ],\n",
       "        [ 62.  ],\n",
       "        [133.  ],\n",
       "        [ 51.  ],\n",
       "        [ 45.  ],\n",
       "        [ 75.5 ],\n",
       "        [ 69.5 ],\n",
       "        [ 75.69],\n",
       "        [ 95.3 ]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y\n",
    "np.mat(Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[90.581875  ],\n",
       "        [47.91694098],\n",
       "        [29.95528193]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W = standRegres(X,Y)\n",
    "W"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2.3 结果可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h_price =X*W\n",
    "h_price=h_price.flatten().A[0] # 将矩阵matrix对象转换为数组array对象\n",
    "h_price = h_price.reshape(-1)\n",
    "\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.plot(label_mat, marker = 'o', label = '真实房价')\n",
    "plt.plot(h_price, marker = '.', label='预测房价')\n",
    "plt.xlabel('样本序号', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize=25)\n",
    "\n",
    "plt.legend(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 测试算法\n",
    "\n",
    "使用$R^{2}$或者预测值和数据的拟合度，来分析模型的效果"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算假设房价与实际房价的相关度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.89802378],\n",
       "       [0.89802378, 1.        ]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(h_price,label_mat.reshape(1,-1))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6 使用算法\n",
    "使用回归，在给定的时候预测出一个数值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "area = 110  # 面积\n",
    "room = 1  # 房间数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对输入变量进行标准化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "x0 = 1\n",
    "x1 = (area - house_mat[:,0].mean())/(house_mat[:,0].max() - house_mat[:,0].min()) \n",
    "x2 = (room - house_mat[:,1].mean())/(house_mat[:,1].max() - house_mat[:,1].min())  \n",
    "\n",
    "X = [x0,x1,x2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[84.20052784]]\n"
     ]
    }
   ],
   "source": [
    "h_price = X*W\n",
    "print(h_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 0.1598639455782312, -0.46875]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 局部加权线性回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "num = len(house_mat)\n",
    "x0 = np.ones(num) # 生成一行全1的数组作为x0\n",
    "x1 = (house_mat[:,0] - house_mat[:,0].mean())/(house_mat[:,0].max() - house_mat[:,0].min())           #对房间面积进行标准化\n",
    "x2 = (house_mat[:,1] - house_mat[:,1].mean())/(house_mat[:,1].max() - house_mat[:,1].min())            #对房间数进行标准化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.stack((x0,x1,x2), axis = 1)\n",
    "Y = label_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lwlr(testPoint,xArr,yArr,k=1.0):\n",
    "    #x和y是训练集样本\n",
    "    xMat = np.mat(xArr); yMat = np.mat(yArr)\n",
    "    #m是样本个数\n",
    "    m = np.shape(xMat)[0]\n",
    "    #创建一个对角单位矩阵用来保存权重w\n",
    "    #使用矩阵而不是向量的原因是为了最后用矩阵乘法好算，公式里面也是这样写的\n",
    "    weights = np.mat(np.eye((m)))\n",
    "    for j in range(m):                      #next 2 lines create weights matrix\n",
    "        #一个样本计算一遍，填到weight中\n",
    "        diffMat = testPoint - xMat[j,:]     #\n",
    "        weights[j,j] = np.exp(diffMat*diffMat.T/(-2.0*k**2))\n",
    "    xTx = xMat.T * (weights * xMat)\n",
    "    if np.linalg.det(xTx) == 0.00000:\n",
    "        print (\"This matrix is singular, cannot do inverse\")\n",
    "        return\n",
    "    ws = xTx.I * (xMat.T * (weights * yMat))\n",
    "    return testPoint * ws\n",
    "#对多个待回归点进行回归\n",
    "def lwlrTest(testArr,xArr,yArr,k=1.0):  #loops over all the data points and applies lwlr to each one\n",
    "    m = np.shape(testArr)[0]\n",
    "    yHat = np.zeros(m)\n",
    "    for i in range(m):\n",
    "        yHat[i] = lwlr(testArr[i],xArr,yArr,k)\n",
    "    return yHat\n",
    "#输出x和y坐标，比lwlrTest更方便将结果画出来\n",
    "def lwlrTestPlot(xArr,yArr,k=1.0):  #same thing as lwlrTest except it sorts X first\n",
    "    yHat = np.zeros(np.shape(yArr))       #easier for plotting\n",
    "    xCopy = np.mat(xArr)\n",
    "    xCopy.sort(0)#按第一个特征排个序\n",
    "    for i in range(np.shape(xArr)[0]):\n",
    "        yHat[i] = lwlr(xCopy[i],xArr,yArr,k)\n",
    "    return yHat,xCopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:12: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  weights[j,j] = np.exp(diffMat*diffMat.T/(-2.0*k**2))\n",
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:24: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  yHat[i] = lwlr(testArr[i],xArr,yArr,k)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([138.91463632,  91.03982024,  93.58739383, 117.27343511,\n",
       "        66.37284122,  93.76973227, 116.76660471,  85.11455429,\n",
       "        89.19109149, 139.04120106,  53.49874075,  43.93679929,\n",
       "        69.26534963,  65.84040446,  81.41160343,  87.39264313])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lwlrTest(X,X,Y,0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:12: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  weights[j,j] = np.exp(diffMat*diffMat.T/(-2.0*k**2))\n",
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:24: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  yHat[i] = lwlr(testArr[i],xArr,yArr,k)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h_price =X*W\n",
    "h_price=h_price.flatten().A[0] # 将矩阵matrix对象转换为数组array对象\n",
    "h_price = h_price.reshape(-1)\n",
    "\n",
    "plt.figure(figsize=(10,8))\n",
    "plt.plot(label_mat, marker = 'o', label = '真实房价')\n",
    "plt.plot(h_price, marker = '.', label='预测房价')\n",
    "plt.plot(lwlrTest(X,X,Y,0.5), marker = '.', label='局部加权预测房价')\n",
    "plt.xlabel('样本序号', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize=25)\n",
    "\n",
    "plt.legend(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:12: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  weights[j,j] = np.exp(diffMat*diffMat.T/(-2.0*k**2))\n",
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:24: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  yHat[i] = lwlr(testArr[i],xArr,yArr,k)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,12))\n",
    "srtInd = X[:,1].argsort(0)\n",
    "xSort = X[srtInd]\n",
    "\n",
    "ySort = lwlrTest(X,X,Y,1)[srtInd]\n",
    "plt.subplot(2,2,1)\n",
    "plt.title(\"k=1\",fontsize=15)\n",
    "plt.xlabel('面积', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "plt.plot(xSort[:,1],h_price[srtInd], label='预测房价')\n",
    "plt.scatter(X[:,1],Y.T,c='red')\n",
    "plt.plot(xSort[:,1],ySort, label='局部加权预测房价')\n",
    "plt.legend(fontsize=15)\n",
    "\n",
    "ySort = lwlrTest(X,X,Y,0.7)[srtInd]\n",
    "plt.subplot(2,2,2)\n",
    "plt.title(\"k=0.7\",fontsize=15)\n",
    "plt.xlabel('面积', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "plt.plot(xSort[:,1],h_price[srtInd], label='预测房价')\n",
    "plt.scatter(X[:,1],Y.T,c='red')\n",
    "plt.plot(xSort[:,1],ySort, label='局部加权预测房价')\n",
    "plt.legend(fontsize=15)\n",
    "\n",
    "ySort = lwlrTest(X,X,Y,0.3)[srtInd]\n",
    "plt.subplot(2,2,3)\n",
    "plt.title(\"k=0.3\",fontsize=15)\n",
    "plt.xlabel('面积', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "plt.plot(xSort[:,1],h_price[srtInd], label='预测房价')\n",
    "plt.scatter(X[:,1],Y.T,c='red')\n",
    "plt.plot(xSort[:,1],ySort, label='局部加权预测房价')\n",
    "plt.legend(fontsize=15)\n",
    "\n",
    "ySort = lwlrTest(X,X,Y,0.1)[srtInd]\n",
    "plt.subplot(2,2,4)\n",
    "plt.title(\"k=0.1\",fontsize=15)\n",
    "plt.xlabel('面积', fontsize = 25)\n",
    "plt.ylabel('房价', fontsize = 25)\n",
    "plt.plot(xSort[:,1],h_price[srtInd], label='预测房价')\n",
    "plt.scatter(X[:,1],Y.T,c='red')\n",
    "plt.plot(xSort[:,1],ySort, label='局部加权预测房价')\n",
    "plt.legend(fontsize=15)\n",
    "\n",
    "         \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:12: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  weights[j,j] = np.exp(diffMat*diffMat.T/(-2.0*k**2))\n",
      "C:\\Users\\huaili\\AppData\\Local\\Temp\\ipykernel_28420\\3334238677.py:24: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  yHat[i] = lwlr(testArr[i],xArr,yArr,k)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[1.       , 0.9412367],\n",
       "       [0.9412367, 1.       ]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(lwlrTest(X,X,Y,0.1),label_mat.reshape(1,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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